information behavior research paper

Mapping the interdisciplinarity in information behavior research: a quantitative study using diversity measure and co-occurrence analysis

• Published: 11 April 2020
• Volume 124 , pages 489–513, ( 2020 )

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• Shengli Deng 1 &
• Sudi Xia 1  

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Information behavior research is an interdisciplinary field in essence due to the investigation of interdisciplinary in previous work. To track the changes in interdisciplinarity of this field, more efforts should be put on basis of previous work. Based on publications searched from Web of Science from 2000 to 2018, we explored the interdisciplinarity of this field drawing on network analysis and diversity measure. Findings showed that although variety of disciplines in this field augmented significantly, the distribution of disciplines is unbalanced and concentrated on some dominant disciplines such as computer science, engineering, psychology, social science and medicine, etc. Relationships among disciplines have evolved over time and mainly focused on neighboring disciplines instead of distinct disciplines. Computer science, engineering, psychology, health science and social science function as intermediate disciplines connecting distinct disciplinary groups. Besides, the measurement using diversity measure shows that interdisciplinary degree of this field appears to decrease. This study contributes to the evolution and measurement of interdisciplinarity of information behavior research, which has implications for researchers and practitioners in this field.

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Deng, S., Xia, S. Mapping the interdisciplinarity in information behavior research: a quantitative study using diversity measure and co-occurrence analysis. Scientometrics 124 , 489–513 (2020). https://doi.org/10.1007/s11192-020-03465-x

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Links relacionados, versión on-line  issn 2301-1378, infor vol.28 no.1 montevideo  2023  epub 01-jun-2023, https://doi.org/10.35643/info.28.1.5  .

Dossier Comportamiento humano informacional

Information Behavior Research in the twenty-first century: The journey so far

La investigación del comportamiento de la información en el siglo XXI: el viaje hasta ahora

Pesquisa de comportamento informacional no século XXI: a jornada até agora

1 Professor and Director, Information Science & Technology Concentration, School of Library and Information Science, Simmons University, Boston, USA, [email protected]

Information behavior describes the many ways in which human beings interact with information - how people seek and utilize information, but also includes other activities such as avoiding/stopping, distorting, encountering by chance, organizing, storing, creating, sharing, diffusing, and deciding to stop using information. Prior studies have attempted to review the history of information seeking and information behavior research in the past 50-60 years. While there have been recent studies looking at different aspects of information behavior, there is a need to bring the key conclusions from these together in one place. This paper seeks to answer the question, “What is the trajectory of information behavior research in the 21st century? What are some of the future directions?” The unit of analysis is research articles published on information behavior between the years 2000 and 2023. These include papers published in Information Research, the Journal of the Association for Information Science and Technology, and those presented in Information Seeking in Context conferences and the Annual Meetings of the Association for Information Science and Technology, and research on information behavior models and context. While not meant to be exhaustive, this paper should bring new and existing researchers up to speed on some of the recent developments in the field during the past two decades.

Keywords:  information behavior; twenty-first century; context; information behavior models; theories; future trends

El comportamiento de la información describe las muchas formas en que los seres humanos interactúan con la información: cómo las personas buscan y utilizan la información, pero también incluye otras actividades como evitar/detener, distorsionar, encontrar por casualidad, organizar, almacenar, crear, compartir, difundir y decidir. para dejar de usar la información. Estudios previos han intentado revisar la historia de la búsqueda de información y la investigación del comportamiento de la información en los últimos 50-60 años. Si bien se han realizado estudios recientes que analizan diferentes aspectos del comportamiento de la información, existe la necesidad de reunir las conclusiones clave de estos en un solo lugar. Este artículo busca responder a la pregunta: “¿Cuál es la trayectoria de la investigación del comportamiento de la información en el siglo XXI? ¿Cuáles son algunas de las direcciones futuras? La unidad de análisis son los artículos de investigación publicados sobre el comportamiento de la información entre los años 2000 y 2023. Estos incluyen artículos publicados en Information Research, Journal of the Association for Information Science and Technology, y los presentados en las conferencias Information Seeking in Context y las reuniones anuales. de la Asociación para la Ciencia y la Tecnología de la Información, y la investigación sobre modelos y contexto de comportamiento de la información. Si bien no pretende ser exhaustivo, este documento debería poner al día a los investigadores nuevos y existentes sobre algunos de los desarrollos recientes en el campo durante las últimas dos décadas.

Palabras clave:  comportamiento de la información; siglo veintiuno; contexto; modelos de comportamiento de la información; teorías; futuras tendencias

O comportamento informacional descreve as várias maneiras pelas quais os seres humanos interagem com a informação - como as pessoas buscam e utilizam a informação, mas também inclui outras atividades, como evitar/parar, distorcer, encontrar por acaso, organizar, armazenar, criar, compartilhar, difundir e decidir parar de usar informações. Estudos anteriores tentaram revisar a história da busca de informações e da pesquisa de comportamento informacional nos últimos 50 a 60 anos. Embora existam estudos recentes que analisam diferentes aspectos do comportamento da informação, é necessário reunir as principais conclusões deles em um só lugar. Este artigo procura responder à pergunta: “Qual é a trajetória da pesquisa de comportamento informacional no século XXI? Quais são algumas das direções futuras?” A unidade de análise são artigos de pesquisa publicados sobre comportamento informacional entre os anos 2000 e 2023. Isso inclui artigos publicados em Information Research, Journal of the Association for Information Science and Technology e aqueles apresentados em conferências Information Seeking in Context e Annual Meetings da Association for Information Science and Technology, e pesquisa sobre modelos e contexto de comportamento da informação. Embora não pretenda ser exaustivo, este documento deve atualizar os pesquisadores novos e existentes sobre alguns dos desenvolvimentos recentes no campo durante as últimas duas décadas.

Palavras-chave:  comportamento informacional; século XXI; contexto; modelos de comportamento informacional; teorias; tendências futuras

Introduction

Information behavior describes the many ways in which human beings interact with information - how people seek and utilize information ( Bates, 2017 ), but also includes other activities intentional/active and unintentional/passive activities ( Wilson, 1999 ) such as avoiding/stopping, distorting, encountering by chance, organizing, storing, creating, sharing, diffusing, and deciding to stop using information ( Agarwal, 2022 ). “It includes face-to-face communication with others, as well as the passive reception of information as in, for example, watching TV advertisements, without any intention to act on the information given.” ( Wilson, 2000 , p. 49). The term came into wide use in the 1990s to replace earlier terms such as “information seeking” ( Bates, 2017 ) or as a shorthand for the longer “information needs, seeking, and use” or INSU ( Courtright, 2007 ).

Prior studies have attempted to review the history of information seeking and information behavior research in the past 50-60 years (see for example, Case and Given, 2016 ; Bates, 2017 ). While there have been recent studies looking at different aspects of information behavior, there is a need to bring the key conclusions from these together in one place, summarizing the more recent developments in this field in the twenty-first centurySome of the recent studies are listed here. VanScoy et al. (2022 ) looked at theory usage in empirical research in the papers published in the Information Seeking in Context conference between 1996 and 2020. Agarwal & Islam (2020 ) carried out a bibliometric analysis of articles published in the Journal of the Association for Information Science and Technology during the last two decades. Islam and Agarwal ( 2022 ) did a similar bibliometric analysis of papers published in the Proceedings of the Annual Meeting of the Association for Information Science and Technology during the last twenty years. Agarwal ( 2022 ) looked at information seeking behavior models and integrated models developed after the year 2000 (but also included models before 2000). Greifeneder & Schlebbe (2022 ) proposed a general model of the information behavior field. Case and Given (2016 ) include information seeking behavior research from the first decade of the twenty-first century. Ford (2015 ), Wilson (2020 ), and Jean, Gorham, & Bonsignore (2021 ) focus on the understanding of information behavior. Agarwal (2018 ) includes a comprehensive listing of information behavior research, especially as it relates to the context of human information behavior. Tang et al. (2021 a, 2021b ) cover paradigm shifts in information behavior research. Bates ( 2022 ) summarizes the research focal points of information seeking metatheories.

This paper seeks to answer the question, “What is the trajectory of information behavior research in the 21st century? What are some of the future directions?” The unit of analysis is research articles published on information behavior between the years 2000 and 2023. These include papers published in Information Research, the Journal of the Association for Information Science and Technology ( Agarwal and Islam, 2020 ), and those presented in Information Seeking in Context conferences and the Annual Meetings of the Association for Information Science and Technology ( Islam and Agarwal, 2022 ), research on information behavior models ( Agarwal, 2022 ; Greifeneder & Schlebbe, 2022 ), theories ( VanScoy et al., 2022 ; Bates, 2022 ), and context ( Agarwal, 2018 ), and other related research.

While not meant to be exhaustive, this paper should bring new and existing researchers up to speed on some of the recent developments in the field during the past two decades. The rest of the paper is organized as follows. The next section includes a literature review. This is followed by methodology, and then the main contribution of the paper - highlights of information behavior research from 2000-2023. This is followed by future trends and directions. The last section on discussion and conclusions also includes limitations and implications.

2. Literature Review

This section focuses on two major themes - information science and metatheoretical approaches in information behavior research.

Information Science

Information behavior is a stream of research within the wider field of information science. An understanding of information science helps us understand information behavior better. At the inaugural Information Science summit organized jointly by the Association for Information Science and Technology (ASIS&T), the Association for Library and Information Science Education (ALISE), iSchools, and the Special Libraries Association (SLA) on October 28, 2022 in Pittsburgh, Pennsylvania, a panel of iFederation Leaders (representing ASIS&T, ALISE, and iSchools), Deans, Directors, and Chairs discussed “What is information science?” ( IS Summit, 2022 )

Gary Marchionini, Dean, University of North Carolina, Chapel Hill described information as intellectual energy and information science as the study of the genesis, organization, flow, use, and preservation of intellectual energy and its impact on humanity. Michael Seadle, Professor, Berlin School of Library and Information Science described information science as a philosophy where we understand information as something as broad and integral as historians understand the relationship with the past. He said that what we study in information science are the relationships between this thing called information which has context as well as data. Vivek Singh, Associate Professor, Rutgers School of Communication and Information, defined information science as a study of the intersection between humans and information, especially in an age of abundance. Recalling the movie Forrest Gump, Abebe Rorissa, Director, University of Tennessee, Knoxville described information science as what information science does. Rong Tang, President, ALISE, said that information science has the component of scholarship and study, but added the professional practice component to it - the applied and practice context that information science is contextualized in. In the panel in his role as President of ASIS&T, the author described information science as a triangle with three ends - human (that Brenda Dervin described in phenomenological terms as a “body-mind-heart-spirit moving through time and space, with a past history, present reality, and future dreams or ambitions.”, Foreman-Wernet, 2003 , p.7; Agarwal, 2012 ), information, and technology. Since most of the world is interacting with information often mediated by technology, he defined information science as the “entire world”. Sanda Erdelez, Chair, iSchools and Interim Dean, College of Organizational, Computational, and Information Sciences, Simmons University described information science as a systematic study of information and systems in which reside information, people that interact with the information, and the social contexts in which these people exist - an ever-evolving field with a target that we don't know where it is. ( Agarwal, 2022b )

Metatheoretical approaches in information behavior research

Agarwal (2022 ) reviews the major metatheories used in human information behavior research. He concludes that cognitive and social approaches are the two basic streams in the conceptual development of information seeking (and other forms of information behavior) focusing on the central role of the user, though there are others, such as affective approaches (e.g., see Nahl and Bilal, 2007 ; Savolainen, 2014 ) that study the role of emotion in information seeking and system-centered approaches. Cognitive approaches, which cover conscious intellectual activity, focus on the interactions between the user and the system and are concerned with user attributes and knowledge structures ( Belkin, 1990 ; Agarwal, 2022 ). Social approaches focus on the user’s social context and include collaboration or collaborative information seeking ( Shah, 2012 ). Multifaceted approaches cover the cognitive, social, and organizational context ( Pettigrew, Fidel, and Bruce, 2001 ; Ingwersen and Järvelin, 2005 ). Agarwal (2018 ) classifies the views of context as personal view (combining cognitive and affective approaches), shared view (social approach), and stereotyped view (primarily cognitive). Agarwal ( 2014 ) discusses the idea of embodiment where a child interacting with a smartphone or tablet is part of a context that is embodied within a larger physical context of a room or a backyard. Agarwal (2018 )discusses how embodiment enables portability where a person talking on the phone can walk out of the airport with a continuity of engagement with the person one is speaking with on the phone but having a change in physical surroundings. A preliminary understanding of these helps us view the developments in information behavior research in the twenty-first century as combining one or more of these metatheoretical approaches.

In the 2020 ASIS&T SIG USE Symposium, Jenna Hartel made a presentation on the major turns in the Information Science field based on her paper “Turn turn turn” ( Hartel, 2019 ) - the cognitive turn, the affective turn, the neo-documentary turn, the socio-cognitive turn, the everyday life turn, the social constructionist turn, and the embodied turn ( Agarwal & Franco, 2021 ). The following is a summary of seven turns in LIS by Hartel ( 2019 ). The cognitive turn in the 1980s featured a turn from the system-centered era to a user-system approach, with the user and their thought world becoming the foremost object of inquiry. In the affective turn of the 1990s, the user or the actor's emotional experience became a matter of keen interest. The neo-documentary turn of the 1990s focused on the properties and types of documents, their social and cultural construction within many different contexts, their changing nature in the digital age, and applied problems of documentation like retrieval, annotation, preservation, authorship, identity, intellectual property, etc. Another turn of the 1990s, the socio-cognitive turn, shifted attention from individual and internal knowledge structures to the outward and social construction of knowledge within communities in social, organizational, and professional contexts. Researchers in the everyday life turn sought to understand and celebrate information phenomena associated with routine or pleasurable and profound life experiences. In the early 2000s, proponents of the social constructionist turn argued that library and information science should define its subject matter as conversations, not information. The embodied turn in the mid-2000s focuses on the role of the body as the subject of research in the field and shows the natural logical step in the progression from the mind, heart, and body within LIS, aiming for a holistic understanding of the human information experience ( Hartel, 2019 ).

Figure 1:  Research focal points of information seeking metatheories 

Bates (2022 ) models information in relation to human beings in six frameworks-the self , the thinking, motivated being, within the body , existing in a physical ecology that is shaped by society - all the social and cultural elements of human existence, discourse , and documentation , and places sixteen methodological and theoretical metatheories in relation to these frameworks. See Figure 1 . Bates describes it as a simplified diagram of the various principal domains where various theoretical and methodological approaches have concentrated their attention on considering the role of information in human life. Bates says that the display is approximate, with information being the unique core of our field, that could be studied from many directions and perspectives. Using any one of the metatheories, a researcher will be able to trace the role or impact of information in human life and institutions from the perspective of that metatheory ( Bates, 2022 ).

3. Methodology

This study primarily adopts a literature review method for gathering evidence. While the study can be seen as a long and detailed literature review, it would be useful to classify it as belonging to a particular type of literature review. Grant and Booth (2009 ) present a typology of 14 types of reviews of the literature, including their associated methodologies, key characteristics, and perceived strengths and weaknesses. Based on their typology, the review method utilized in this study can be seen as an umbrella review . Such a method refers to a review compiling evidence from multiple reviews into one accessible and usable document. It focuses on a broad condition or problem for which there are competing interventions and highlights reviews that address these interventions and their results. There is the potential for greater use of such overarching reviews as a mechanism for aggregating findings from several systematic reviews that address specific questions ( Grant and Booth, 2009 ). While umbrella reviews typically identify component reviews but do not include searches for primary empirical studies, this paper utilizes primary studies as well in some cases.

The sources utilized in this paper for an umbrella review include the following primarily (that are listed in parentheses; some of the acronyms used in this section are explained in the rest of the paper):

-unified models of information behavior ( Agarwal 2022 ; Greifeneder & Schlebbe, 2022 )

-context in Information behavior ( Agarwal, 2018 )

-analysis of JASIST proceedings ( Agarwal & Islam, 2020 ) and ASIS&T conference proceedings ( Islam & Agarwal, 2022 )

-theory usage in empirical research in ISIC conference papers ( VanScoy et al., 2022 )

-metatheoretical approaches ( Agarwal, 2022 ; Bates, 2022 )

-definitions for information science (panel at 2022 Information Science Summit - Agarwal, 2022 b)

-impact ( Wilson, 2020 )

-future trends ( Tang et al., 2021 a, 2021b , ARIST call for submissions, and other sources)

Apart from reviews, specific primary sources were utilized, as appropriate. Content analysis (see Krippendorff, 2018 ) was a suitable method for the following portions as it helped in creating word clouds summarizing the major topics researched in information behavior since the year 2000. Along with an umbrella review, the study utilizes the content analysis method for:

-analyzing titles of papers published in the journal, Information Research. This involved creating and populating a spreadsheet compiling the paper titles and links to papers for each paper published in each number and volume of the journal from 2000 to 2023.

-identifying future directions. This involved analyzing titles of posters and papers published in ASIS&T 2022, ISIC 2022, and CoLIS 2022 conferences.

Information Research (which includes proceedings of ISIC and CoLIS conferences) is used as a major source for this paper as it is a top journal dedicated to information behavior research, which is the subject of this paper. JASIST is a top journal in information science and technology, and the ASIS&T annual meeting is a primary conference organized by ASIS&T that brings together researchers in this field.

A lot of the author’s work (e.g., Agarwal, 2018 , 2022 ) has been about synthesizing the contradictions in our field. Thus, you find these listed above. When writing this article, he debated over referring to his works in the first or the third person. To maintain consistency with the rest of the references, he has chosen the third person when citing himself in the paper.

4. Information behavior research in the twenty-first century

To highlight the key threads in information behavior research from 2000-2023, this section focuses on these areas: unified models of information behavior, context in information behavior, analysis of titles of papers published in Information Research, analysis of JASIST and ASIS&T proceedings, and theory usage in empirical research in ISIC conference papers.

Unified models of information behavior

Agarwal (2022 ) proposed a unified model of information seeking behavior that he arrived at by mapping various common elements of information seeking in the past few decades.

Source: Agarwal, 2022

Figure 2  A unified model of information seeking behavior Arrows indicate sequence. Dotted arrows indicate actions which may or may not occur. Numbers identify elements. Person, source and context have the same number, as person and source are part of context. M1, M2, M3 and M4 are moredating variables 

The model shows a person or a user (labeled 1 in the figure) who engages in a seeking (3) or searching task from various information sources (1) when confronted with a need (2) for information that arises in a certain work or everyday life context (1). The person evaluates and processes (4) the information received and reformulates (5) the query to help answer more questions that arise. At some point, the person may decide to give up (6) searching for more information, and use (6) or share (7) the information that is retrieved. The various steps in this information behavior may be affected by a series of moderators labeled M1, M2, M3, and M4 in Figure 2 .

Agarwal (2022 ) compared the common elements in different models of information seeking/behavior from the year 2000 onwards (also before that) and arrived at a table that included these various elements of Figure 2 . Tables 1 a and 1b below show these common elements mapped to nine models that Agarwal chose to compare in his paper. The first few rows in the table map to the context variables of environment, role, task, situation, person, source, and system, which all affect the information seeking behavior. These are followed by the terms used in the models that relate to information need, seeking/searching, evaluating/processing, use, and sharing of information. He then lists the specific type of information behavior exhibited in the models. Finally, he classifies each model based on the metatheoretical approach used in it, whether cognitive, social, affective or a combination of these.

Table 1a:  Comparing models 

Table 1a:  Following 

Table 1b:  Comparing models 

Table 1b:  Following 

Agarwal extends his unified model of information seeking behavior to include other forms of information behavior, other than seeking and searching. These other behaviors include information avoidance, stopping (Agarwal & Lu, 2020; Agarwal, Mitiku, & Lu, 2022 ), distortion ( Agarwal & Alsaeedi, 2021 ), serendipitous information encountering (see Agarwal, 2015; Agarwal, Huang, & Erdelez, 2021 ), information organization, storing, disuse, information creation, information diffusion ( Agarwal & Alsaeedi, 2021 ), as well as the user collaborating ( Shah, 2012 ; Agarwal & Rahim, 2019 ) with another person on a task or project. See Figure 3 .

Figure 3:   A unified model of information behavior Bold indicates other information behaviors. Arrows indicate sequence. Dotted arrows indicate actions which may or may not occur. Numbers identify elements.Person, source and context have the same number, as person and source are part of context. M1, M2, M3 and M4 are moderating variables 

Greifeneder & Schlebbe (2022 ) also propose a general model of the information behavior field combining information behavior, information experience, and information practice. They list the various ways in which humans interact with information (which they call information use) and how humans do not interact with information (which they call information non-use). They term information behavior as the totality of the (non-)interaction of humans with information. See Figure 4 .

Source: Greifeneder & Schlebbe, 2022

Figure 4  A general model of the information behavior field  

Context in information behavior

As seen in several definitions of information science (Agarwal, 2022b), information behavior doesn’t exist outside of context. Agarwal (2018 , Chapter 2) includes a detailed literature review of the empirical studies in information behavior and how they have incorporated context. This includes the populations studied (various professions, roles, and different demographics), methods used (quantitative - surveys and experiments, qualitative - interviews/focus groups, ethnography/observation, content analysis, and mixed methods), a detailed analysis of variables studied, type of information behavior studied, and context categories or elements affecting information behavior.

Agarwal (2018 , pp. 125-126) reached certain conclusions about context:

1-Context is of the person or actor engaged in a behavior or activity. This could be any information behavior, such as seeking, searching and retrieval, interaction with a person or a device, serendipitous encountering, collaborative behavior, sharing, use, avoiding, etc. Without the behavior or activity (which also includes rest and inactivity), context doesn’t have much meaning or use. The same person would have a different set of contexts at different points of conversation, behavior, and interaction. Context is always created at the point of interaction ( Dourish, 2004 ).

2-Context is always about the relationship - of the actor with entities outside of the actor or even with themselves.

3-Context is not one “whole” concept, which will look the same from every direction. Depending on who you are, where you’re looking from, and who the actor in question is, context will appear differently to you. Agarwal (2018 ) defines three views of context-the actor’s personal view of context, the shared view of context, and a stereotyped view of context. The first two views may be most used by the interpretivist researcher. The positivist researcher and the system developer may be using the third, stereotyped view. From an analysis of empirical research conducted on information behavior (see Chapter 2 of Agarwal, 2018 ), we can conclude that a majority of the context studied in research is the stereotyped view of context.

As an example of one of the three views of context, Figure 5 shows the shared view of the contextual identity framework. It shows two actors with their own personal contexts of identities and familiar information sources, as well as a shared circle of context between them when they’re engaged in collaborative information behavior (CIB). There are also contexts which they both may not be familiar with - people or information sources which are stereotyped contexts from their points of view.

Source: Agarwal, 2018 , p. 89

Figure 5:  Contextual Identity Framework - shared view of context  

1) The elements of context of an actor engaged in an activity (information behavior/information interaction) include aspects of the environment, task/activity/problem situation, need/information required, actor, source/system/channel, actor/source relationship, and time/space. These elements are significant because they demarcate almost everything affecting information behavior that has been studied in the twenty-first century and before that. Figure 6 shows these seven elements shaped by the three views of context ( Agarwal, 2018 , p. 99). Table 2 (from Agarwal, 2018 , pp. 105-107) lists these elements and examples of variables studied that fall within these respective context elements. Figure 7 shows context elements and variables from the point of view of a researcher studying the information behavior of a group of people (stereotyped view of context).

Figure 6:  Context views and elements 

Table 2 (from Agarwal, 2018 , pp. 105-107) lists these elements and examples of variables studied that fall within these respective context elements.

Table 2:  Context elements and variables studied in information behavior research  

Table 2:  Following  

Source: Agarwal (2018 , pp. 105-106).

Figure 7 shows context elements and variables from the point of view of a researcher studying the information behavior of a group of people (stereotyped view of context).

Figure 7:   Context elements with variables when a researcher is studying the information behavior of a group of people (stereotyped view of context) 

Based on his conclusions, Agarwal (2018 ) defines the context of an actor’s information behavior as consisting of “elements such as environment, task, actor-source relationship, time, etc. that are relevant to the behavior during the course of interaction and vary based on magnitude, dynamism, patterns and combinations, and that appear differently to the actor than to others, who make an in-group/out-group differentiation of these elements depending on their individual and shared identities.” (p.128)

Analysis of titles of papers published in Information Research since 2000

For this paper, we analyzed the titles of 1,314 papers published in Information Research between the years 2000 and 2022. With an average of 4 issues a year published in 22 volumes, 89 issues were published, including a Special Issue in 2023 which had the Proceedings of CoLIS (11th International Conference on Conceptions of Library and Information Science - Oslo Metropolitan University, May 29 - June 1, 2022) and the Proceedings of ISIC (the information behavior conference, Berlin, Germany, September 26-29, 2022).

A word cloud generating tool (https://wordart.com/create) was used to create a word cloud showing the most frequent terms mentioned in the titles of 1,314 papers published in Information Research between 2000 and 2022 (see Figure 8 ). We see that the words information, behavior, research, use, social, health, and seeking are among the most frequent terms used.

Figure 8:  Another word cloud of Information Research paper titles (2000 - 2022) 

Table 3 shows a more detailed analysis of words and their relative sizes/frequencies found in the titles of all papers published in Information Research from 2000-2022. The words shown are in decreasing sizes with information being the most highly referenced word, followed by behavior, research, study, and seeking. From the 999 words generated by the tool (https://wordart.com/create), those with sizes 9 and above were included in the table to keep the table size manageable, while capturing the most frequently cited words in the paper titles.

Table 3:  Word and relative frequencies/sizes 

Table 3:  Following 

Analysis of JASIST and ASIS&T proceedings since 2000

Agarwal and Islam (2020 ) analyzed the bibliographic information of full-length research articles published in the Journal of the Association for Information Science & Technology (JASIST) since the year 2000. Established in 1950, and with an impact factor of 3.275 (2021), JASIST is a premier journal in the Information Science field managed by the 85-year-old Association for Information Science & Technology (ASIS&T). Agarwal and Islam’s study included metrics such as article count, authorship, international collaboration, citations, and topical areas. Data was collected from SCOPUS, the JASIST website, and Scimago. Their findings show that JASIST published 3,052 articles during 2000 - 2020, which got cited 180,608 times (59.18 times per article) until 2020. Joint authorship has been increasing. Of the articles published during this period, 741 (24.27%) were single-authored, while three times more articles (2,311, 75.73%) were jointly authored. International collaboration has also been increasing. Figure 9 shows a graph based on the ratio of journal articles signed by researchers from more than one country for each year until 2018. Barring some years, the graph shows overall upward growth in international collaboration during 1999-2018.

Figure 9:   International collaboration among JASIST authors 1999-2018  

Authors from institutions in 70 countries have published, with most articles from the US, with authorship from China steadily increasing in recent years. See Table 4 .

Table 4:  Share of top 10 countries in authorship of JASIST articles.  

Source: based on Agarwal & Islam, 2020

Figure 10 shows the word clouds based on the titles of the 3,052 articles published by JASIST between 2000 and 2020 that Agarwal & Islam (2020 ) analyzed. The figure shows the word clouds based on article titles for five-year periods, and how these changed over time. For example, in 2000-2004, technology, web, retrieval, and search are among the top words used in the title of JASIST research articles.

Figure 10:  Top words in article titles -five-year periods and 2000-2020  

Following up on Agarwal & Islam (2020 ), Islam & Agarwal (2022 ) analyzed the articles published in the conference proceedings of the Annual Meetings of the Association for Information Science and Technology from 2000 - 2020. Their bibliometric analysis used three data sources (Scopus, ASIS&T proceedings website, and Scimago journal ranking) and a scientific mapping analysis using VOSViewer. The study found 3,129 publications in 21 volumes from 2000-2020, with the number of publications showing a mostly upward trend over time (48 publications in 2000 and 217 publications in 2020; 347 publications in 2000-2004 and 877 publications in 2015-2019). Of all the publications during these 21 years, more than three-quarters (77.57%) were jointly authored. Figure 11 shows the percentage of publications each year that have co-authors from different countries. The graph shows that international collaborations were highest in 2016 with more than a quarter of collaborative publications, with a decline in 2017 and a pickup in 2018 above the high 2006 levels ( Islam & Agarwal, 2022 ).

Figure 11  International collaboration among ASIS&T Annual Meeting proceedings authors 1999-2019  

Islam & Agarwal found that 2,726 articles have been cited 9,705 times in 19 years (they excluded 2005 and 2020 in their analysis based on data available), with an average of 3.6 citations per article. Most authors are from U.S., Canada, and China. Table 5 shows the top 20 author-institution countries (with their ranking in the first column, and the number of publications in the second column).

Source: based on Islam & Agarwal, 2022

To investigate major research topics studied, Islam & Agarwal (2022 ) wanted to see the frequency of all keywords in the ASIS&T proceedings and their co-occurrences (or appearing together) with other keywords. They analyzed the 4,384 keywords that appeared in the proceedings from 2000-2019, excluding 2005. These are visualized in the map of Figure 12 . ‘Social media’ was the most frequent keyword, appearing 103 times, followed by ‘information behavior’ (97) and ‘scholarly communication’ (50). 'Information behavior' here doesn't include the more qualified keywords like ‘information seeking behavior’, 'mobile information behavior', or 'health information behavior' ( Islam & Agarwal, 2022 ).

Figure 12:  Co-occurrences of keywords  

Figure 13 shows the co-citations of cited sources in the ASIS&T proceedings (Islam & Agarwal, 2022 ). The Journal of the Association for Information Science & Technology (JASIST) and Information Processing and Management are the sources most cited in the publications of the ASIS&T Annual Meeting proceedings.

Figure 13:  Co-citation of cited sources  

Theory usage in empirical research in ISIC conference papers (2000 - 2020)

VanScoy et al. (2022 ) analyzed the ISIC conference proceedings from 1996 to 2020 to identify 243 papers that reported empirical research. They used content analysis to determine theory usage (if at all, unsubstantial, or substantial) in the paper and the discipline from which the theory originated (including information science).

Of the 203 empirical research papers in the 11 biennial ISIC conferences from 2000-2020, 156 used theory. Thus, theory usage is in 76.85% or about three-quarters of all papers in the proceedings. Of the papers that used theory to some extent, VanScoy et al. found 69% (1996-2020) to have used theory substantially. They found the papers to have used 229 unique theories, with as many as 53 unique theories used in a single year’s papers in 2012. Between 1996 and 2020, they found 545 instances of theory use, with fewer theories used substantially (203 or 37%) than insubstantially (342 or 63%). Of these 543 instances of theory use in ISIC empirical papers, a vast majority (352 or 64.82%) are from information science while the rest are from other fields - sociology (69 or 12.7%), psychology (44 or 8.1%), communication (33 or 6.08%), business/management (20 or 3.68%), education (10 or 1.84%), and other disciplines (16 or 2.95%).

Table 6:  Models/theories used at least thrice in ISIC empirical papers from 1996-2020 ( VanScoy et al., 2022 ) 

Table 6 (adapted from VanScoy et al., 2022 ) shows the models/theories used in information behavior research ranked from the most popular onwards. For each model/theory, VanScoy et el. list the number of uses in the ISIC conference papers, along with information on how many times such usage was substantial. The top 3 models/theories (those of Kuhlthau, Wilson, and Dervin) were used in all 13 conferences since 1996. These, as well as Ellis’ model, showed peak usage in early conference years, while Savolainen’s model is trending towards more use in recent conferences than in earlier years ( VanScoy et al., 2022 ).

Fisher et al. (2005 ) and Wilson (2020 ) serve as other useful sources for theories in information behavior research. Wilson ( 2020 ) also considered the impact of information behavior research on other fields and found that fields such as computer science, health sciences, information systems, and education have largely imported ideas from information behavior research (76-91%) while exporting some of their ideas to the field (9-24%). A JASIST special issue on information behavior and information practices theory ( Willson, Julien, & Burnett, 2022 ) focused on recent theory development and usage in the information field, continuing the work of Fisher et al. (2005 ).

Future trends and directions

Analyzing recent conference papers, and especially posters, provides a good snapshot of the types of areas that researchers are focusing on in the fields of information science and information behavior. They provide trends for the immediate future.

Figure 14:  Top keywords of interest in recent conference papers and posters 

Table 7:  Top keywords and sub-areas in recent conferences 

The word clouds of Figure 14 (generated using (https://wordart.com/create), show the top keywords studied as reflected in a) the virtual and in-person posters presented at the 85 th Annual Meeting of the Association for Information Science & Technology (ASIS&T 2022); b) the long and short papers presented at ASIS&T 2022; c) the papers presented at ISIC 2022: the information behavior conference; and d) the papers presented at CoLIS 2022: 11th International Conference on Conceptions of Library and Information Science. It is interesting to note that data and Covid are emerging as important keywords of interest in current studies.

Table 7 shows these top keywords in more detail (generated by wordart.com). The table also lists the subject areas classifying the papers as listed in the conference program or proceedings. These subject areas provide more information on the content of the papers as classified by the conference organizers.

Tang et al. (2021 a) discuss paradigm shifts in the field of information. They provide the reasoning and motives (why) for shifting paradigm(s) and specified what new paradigm(s) might be adopted (what) by specific community stakeholders in the information field (who), and the strategies and approaches we might employ to actualize these shifts (how). See Table 8 . The ‘what’ part (second row) of the table states that new paradigms might be theoretical, practice-based, impact-driven, social and cultural-oriented, data-driven, or based on community engagement or diversity, equity, and inclusion (DEI).

Table 8:  Paradigm shifts in the field of information (based on Tang et al., 2021 a) 

The JASIST special issue on paradigm shifts provides examples of a range of new paradigms including critical perspectives, socio-emotional paradigms, methodological paradigms, and technological paradigms ( Tang et al., 2021 b). Examples of critical perspectives in the special issues include fully acknowledging the work of underrepresented or marginalized LIS scholars in existing paradigms ( Cooke & Kitzie, 2021 ), focusing on people as knowers, speakers, listeners, and informants rather than ‘users’ for new understandings of information behavior and information literacy ( Oliphant, 2021 ), and epistemicide or killing/devaluating of a knowledge system happening within our field and the ways we have systematically undermined knowledge systems falling outside of Western traditions ( Patin et al., 2021 ).

A December 2022 call for submissions for the Annual Review of Information Science and Technology (ARIST) which publishes comprehensive and systematic reviews on topics relevant to information science listed new and emerging research topics of potential interest such as the rise of “big data” and machine learning; social media platforms and social change (e.g., #metoo; #blacklivesmatter); misinformation and disinformation; implications of COVID-19 on health information seeking; and youth engagement with social media platforms (e.g., Tik Tok).

Misinformation, disinformation, and fake news is certainly a topic of current and continuing interest with the coining of the term ‘infodemic’ where technological and social media advancements have led to ease of automation of false narratives. Agarwal & Alsaeedi (2021 ) propose a model of misinformation behavior , while Wilson (2020 ) calls the phenomenon information misbehavior (pp. 15-16, 30-31).

Figure 15:  Disinformation behavior framework ( Agarwal & Alsaeedi, 2021 ) 

Figure 15 shows Agarwal & Alsaeedi (2021 )’s disinformation behavior framework on the fake news phenomenon and ways to fight it. Misinformation is false information while disinformation is intentially false information. When applied to news, the phenomenon is termed fake news. As per the framework, all false information arises within a certain context such as national elections, COVID-19 pandemic, etc., where, depending upon the intentions of creators and spreaders of false information, algorithms, bots, and social media can be used to deceive. Fake news spreads over time, aided by those who create and spread it, with the intention of influencing outcomes or changing historical narratives. The person or user, as a consumer of information, and depending on their judgement of the credibility and reliability of information and sources (where such judgment is, in turn, affected by one’s confirmation biases and propensity to believe in false narratives) might decide to use, ignore, forward or spread this (mis/dis)information. All this happens within a filter bubble or an echo chamber that the user resides in, where their sources of information such as social media contacts or news media they consume, might further reinforce the user’s biases. The framework proposes ways to fight false information through advococy, critical thinking and action, information/media literacy, and tests for serendipity to determine if the information encountered is truly serendipitous or planted for the user to consume. These methods would help in puncturing the user’s filter bubble.

The phenomenon described above can be further informed by different perspectives. First, Agarwal & Alsaeedi (2021 )’s framework does not address the cost or price of puncturing filter bubbles. While a number of studies have cited the difficulty in fighting false information (comparable to fighting rain by holding an umbrella and hoping not to get wet), they have not always looked at what happens when one is relatively successful in puncturing filter bubbles. A December 26, 1962 cartoon by R.K. Laxman which reads, “Of course you weren’t spreading rumours - the charge is you were spreading facts!”, points to the dangers faced by individuals in different countries and societies who risk being targeted for speaking truth to power and challenging false narratives. Second, while most studies in information behavior in the past two decades have looked at the user as the seeker of information and information sources as ‘giving’ or ‘informing’, studies can also look at the user as one not just consuming but forwarding, spreading, and disseminating false information, either because one is unaware, or with an aim to ‘misinform’ or ‘disinform’. Thus, it can be argued that there is a paradigm shift in the way in which those who 'use' information are influenced by the interests of those creating and spreading false information. Future research can study the disinformation and fake news phenomenon from these perspectives as well.

Contemporary research and writing have frequently focused on how smartphones disconnect us from our physical environment and the people present in the room (e.g., Turkle, 2011 ; Powers, 2011 ). This follows from research on information overload and the recommendations to unplug from technology. Yet, there is a digital disconnect happening as well - almost daily, people choose not to respond to certain messages or calls, which can make the sender anxious, and adversely affect their communication. Recent research has looked at the receiver’s reasons for not responding ( Agarwal, Mitiku, & Lu, 2022 ), and the psychological impact on the sender ( Agarwal & Lu, 2020 ) and on the other communication that they have with themselves and with other people. Research in information behavior has not typically looked at this area of non-response behavior, information avoidance behavior, and information-stopping behavior, which impact the social media communication and mental health of a large number of people using smartphones. More research is needed in this area.

The quick transfer of information enabled by the internet and social media has also led to an accelerated ability to transfer hate. E.g., the aftermath of a court verdict in January 2023 led to mobilization and the intense othering of a particular community in the state of Sikkim in India. An emotive piece seeking to heal divides ( Agarwal, 2023 a) was largely received positively by members of various communities, but also met with rejection in social media comments in some places (e.g., the Facebook comments under Agarwal, 2023b ) that included a widely publicized rebuttal justifying exclusiveness as opposed to inclusiveness. This points to the continuing difficulties in diversity, equity, inclusion, and accessibility (DEIA) work in parts of the world. The opportunities and challenges for DEIA and the role of social media should be research topics of continuing interest.

A lot of research in 2020 and 2021 focused on COVID and information behavior surrounding it. While many world events have taken place in the recent past, COVID has changed the world in fundamental ways, including most people either experiencing the loss of loved ones or knowing family or friends who would have experienced that loss. This has brought about a greater mainstream realization of the fragility of human life and how people are struggling in different ways. Another effect has been a more widespread comfort of doing things online, moving many people and workplaces towards a hybrid way of working. COVID is likely to be around in the future as well, though hopefully, in a more manageable form. Thus, one topic of continuing interest would be how the information behavior of people has changed after the 2020/2021 COVID experience.

There have been studies on information behavior related to climate change, related immigration/migration ( Balsari, Dresser, & Leaning, 2020 ), and climate change skepticism and debate ( Foderaro & Lorentzen, 2023 ). These areas will remain important for future research.

Other topics of interest would be health and fitness, big data, artificial intelligence, and ChatGPT, serendipity versus productivity (see Sunoo, Erdelez, & Agarwal, 2023 who discuss how productivity apps can also be used to facilitate information encountering and serendipity, which help creativity and innovation), mental health and happiness, people’s information worlds with pets and the embodied aspects of information in such relationships ( Solhjoo, 2022 ), and the role of human-information-technology interactions in all these phenomena.

Discussion and Conclusions

This was an ambitious paper seeking to understand what has gone on within information behavior research since the advent of the twenty-first century, and what the future might look like. One way was to go through every single paper that has been published in this area in the past twenty-three years. This may not have been feasible in a timely fashion. Another way was to try and summarize the key findings from some of the major studies that have synthesized the research in this area during the past two decades. The task then was to bring them together in a way that is useful to a new researcher trying to understand this area or a seasoned researcher who would benefit from having key findings and arguments in one place. This paper followed the latter approach, while also doing a content analysis of the titles of publications in key journals and conferences of the field.

So, what did we learn? Let us try to summarize the key takeaways from the paper. We learned that the term information science is defined differently by different people who might have different definitions even for what information means. We also learned that there are various ways or perspectives (or metatheories) of looking at the phenomenon ranging from cognitive to social to affective to a mix of various approaches. Each of these perspectives provides a separate lens for trying to understand a phenomenon such as human information behavior.

We also see that many models have emerged in the information seeking and information behavior areas, as well as models that have tried to integrate these together. Agarwal (2022 ) has tried to unify these in a single model. At the heart of the each of these various models is the centrality of the person or the actor, who is often seen as a searcher of information, a person accessing different types of information, who might use information or give up - but increasingly this person is also seen as diverse, having intersectional identities, and is trying to make sense of the world and all the information that emanates from it. Some of this information can be relied upon, and a large portion of it may either be deliberately or inadvertently false or too much for a person’s mind to handle. This person also may not know what to make of life, especially post-pandemic, and is trying one’s best to sometimes survive and sometimes thrive. They live between physical and digital worlds, one increasingly with virtual and augmented realities, and one affected by artificial intelligence - which can be both a challenge and an opportunity. Such a person also needs to deal with one’s mind and spiritual dimensions that they may experience at times. The person needs to either join or grapple with the cries of “us versus them” or learn to see everyone as themselves - not because people are all similar, but because they are different, and this individual difference is what makes people similar to each other.

Along with the person and the information sources that the person goes to and the information world that they inhabit, a primary aspect of the information behavior field is context. Brenda Dervin called it an “unruly beast” ( Agarwal, 2012 , 2018 ). We understand that context is of a person engaged in an activity - thus, without a specific type of information behavior - whether seeking, searching, evaluating, processing, avoiding, stopping, distorting, organizing, storing, using, disusing, creating, sharing, or encountering information ( Agarwal, 2022 ) in a specific time and place - whether physical or digital or multidimensional/augmented, context has no meaning. The context of this author writing this paper is very different from that of this author picking one’s child from school, buying groceries in the supermarket, or teaching a group of students. Context looks different when viewed from different perspectives and can be reliably seen as consisting of one of seven elements - actor, environment, task/activity/problem situation, need/information required, source/system/channel, actor-source relationship, and time/space ( Agarwal, 2018 ), with most variables studied in information behavior in the twenty-first century being aspects of one or more of these elements.

In most information behavior research, information, not surprisingly, is the most commonly occurring keyword. Thus, seeing ourselves as belonging simply to the information field may not be off the mark. Almost all the other keywords are either activities associated with information such as behavior, research, study, seeking, use, analysis, etc., or domains such as social, library, health, web, and so on.

We also see that authors in our field like to collaborate, and increasingly internationally and that countries outside North America such as China are making their presence felt in the information science literature ( Agarwal & Islam, 2020 ; Islam & Agarwal, 2022 ). There are also calls for fully acknowledging the works of underrepresented and marginalized LIS scholars ( Cooke & Kitzie, 2021 ).

In papers published in venues dedicated to information behavior research such as the biennial Information Seeking in Context conferences, theory usage is as high as three-quarters of all papers in the proceedings ( VanScoy et al., 2022 ). There is still a debate about whether we produce more models and not enough theory, how much we borrow from other disciplines (about 35% of the time; VanScoy et al., 2022 ), and whether we contribute enough to research in other disciplines or not. We seem to have impacted fields such as computer science, health sciences, information systems, and education in certain ways ( Wilson, 2020 ).

esearch trends for the present and future point to the role of information in mobile behavior, big data, disinformation, mixed realities, and DEIA, ethics of artificial intelligence, climate change and migration, among other topics, with several new and existing paradigms ranging from theoretical to practice-based to impact-driven, to socially and culturally oriented to data-driven, and to community engagement based ( Tang et al., 2021 a).

This paper has several limitations. It has provided an umbrella review from the perspective of a single researcher. Several primary sources might have been missed in the process of writing this paper. Second, another researcher in the information behavior field might have a different take on what the field has accomplished in the past two decades. Thus, this paper should be seen as one way or one perspective of looking back at the field, and into the near future. Third, this study has adopted more of a chronological or historical perspective in reviewing the past two decades of research in information behavior. Future research could adopt a more critical perspective. Finally, the reviews consulted are much more detailed. Only the key findings from them are included here. The reader is advised to delve into those sources for a deeper understanding.

This paper should be useful to students and emerging researchers in helping them quickly come up to speed on some of the major developments in the field of information behavior in the past two decades. It could be a useful paper to complement some of the other sources that have looked at information science and information behavior research wholistically such as Case and Given (2016 ), Agarwal (2018 , 2022 ), and Wilson (2020 ). Future research can try to address some of the limitations of this work and include publications or perspectives that might have been missed. Other methods of data gathering such as systematic reviews and metanalyses can also be carried out. As an overarching theme, what we can conclude from this paper is that information behavior research is going to remain increasingly relevant even as the human experience straddles multiple stresses and undergoes profound changes in an ever-dynamic world.

Acknowledgments

This article is dedicated to the memory of Professor Brenda Dervin who was one of the foremost influences in guiding the research of this author since his Ph.D. days, as well as the research and practice of various people in the information science and communication fields. See Agarwal (2023c ) for a tribute and links to her video interviews and her seminal work in the Sense-Making Methodology over decades.

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Editor´s Note : The editor responsible for the publication of this work is Martha Sabelli

Author contribution note : I am the sole author of the article

Received: January 19, 2023; Accepted: April 11, 2023

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Journal of Documentation

ISSN : 0022-0418

Article publication date: 1 August 1999

This paper presents an outline of models of information seeking and other aspects of information behaviour, showing the relationship between communication and information behaviour in general with information seeking and information searching in information retrieval systems. It is suggested that these models address issues at various levels of information behaviour and that they can be related by envisaging a ‘nesting’ of models. It is also suggested that, within both information seeking research and information searching research, alternative models address similar issues in related ways and that the models are complementary rather than conflicting. Finally, an alternative, problem‐solving model is presented, which, it is suggested, provides a basis for relating the models in appropriate research strategies.

• Information retrieval
• Problem solving

Wilson, T.D. (1999), "Models in information behaviour research", Journal of Documentation , Vol. 55 No. 3, pp. 249-270. https://doi.org/10.1108/EUM0000000007145

Copyright © 1999, MCB UP Limited

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• Published: 27 January 2022

The future of human behaviour research

• Janet M. Box-Steffensmeier 1 ,
• Jean Burgess 2 , 3 ,
• Maurizio Corbetta 4 , 5 ,
• Kate Crawford 6 , 7 , 8 ,
• Esther Duflo 9 ,
• Laurel Fogarty 10 ,
• Alison Gopnik 11 ,
• Sari Hanafi 12 ,
• Mario Herrero 13 ,
• Ying-yi Hong 14 ,
• Yasuko Kameyama 15 ,
• Tatia M. C. Lee 16 ,
• Gabriel M. Leung 17 , 18 ,
• Daniel S. Nagin 19 ,
• Anna C. Nobre 20 , 21 ,
• Merete Nordentoft 22 , 23 ,
• Aysu Okbay 24 ,
• Andrew Perfors 25 ,
• Laura M. Rival 26 ,
• Cassidy R. Sugimoto 27 ,
• Bertil Tungodden 28 &
• Claudia Wagner 29 , 30 , 31  

Nature Human Behaviour volume  6 ,  pages 15–24 ( 2022 ) Cite this article

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Human behaviour is complex and multifaceted, and is studied by a broad range of disciplines across the social and natural sciences. To mark our 5th anniversary, we asked leading scientists in some of the key disciplines that we cover to share their vision of the future of research in their disciplines. Our contributors underscore how important it is to broaden the scope of their disciplines to increase ecological validity and diversity of representation, in order to address pressing societal challenges that range from new technologies, modes of interaction and sociopolitical upheaval to disease, poverty, hunger, inequality and climate change. Taken together, these contributions highlight how achieving progress in each discipline will require incorporating insights and methods from others, breaking down disciplinary silos.

Genuine progress in understanding human behaviour can only be achieved through a multidisciplinary community effort. Five years after the launch of Nature Human Behaviour , twenty-two leading experts in some of the core disciplines within the journal’s scope share their views on pressing open questions and new directions in their disciplines. Their visions provide rich insight into the future of research on human behaviour.

Artificial intelligence

Kate Crawford

Much has changed in artificial intelligence since a small group of mathematicians and scientists gathered at Dartmouth in 1956 to brainstorm how machines could simulate cognition. Many of the domains that those men discussed — such as neural networks and natural language processing — remain core elements of the field today. But what they did not address was the far-reaching social, political, legal and ecological effects of building these systems into everyday life: it was outside their disciplinary view.

Since the mid-2000s, artificial intelligence (AI) has rapidly expanded as a field in academia and as an industry, and now a handful of powerful technology corporations deploy these systems at a planetary scale. There have been extraordinary technical innovations, from real-time language translation to predicting the 3D structures of proteins 1 , 2 . But the biggest challenges remain fundamentally social and political: how AI is widening power asymmetries and wealth inequality, and creating forms of harm that need to be prioritized, remedied and regulated.

The most urgent work facing the field today is to research and remediate the costs and consequences of AI. This requires a deeper sociotechnical approach that can contend with the complex effect of AI on societies and ecologies. Although there has been important work done on algorithmic fairness in recent years 3 , 4 , not enough has been done to address how training data fundamentally skew how AI models interpret the world from the outset. Second, we need to address the human costs of AI, which range from discrimination and misinformation to the widespread reliance on underpaid labourers (such as the crowd-workers who train AI systems for as little as US $2 per hour) 5 . Third, there must be a commitment to reversing the environmental costs of AI, including the exceptionally high energy consumption of the current large computational models, and the carbon footprint of building and operating modern tensor processing hardware 6 . Finally, we need strong regulatory and policy frameworks, expanding on the EU’s draft AI Act of 2021.

By building a more interdisciplinary and inclusive AI field, and developing a more rigorous account of the full impacts of AI, we give engineers and regulators alike the tools that they need to make these systems more sustainable, equitable and just.

Kate Crawford is Research Professor at the Annenberg School, University of Southern California, Los Angeles, CA, USA; Senior Principal Researcher at Microsoft Research New York, New York, NY, USA; and the Inaugural Visiting Chair of AI and Justice at the École Normale Supérieure, Paris, France.

Anthropology

Laura M. Rival

The field of anthropology faces fundamental questions about its capacity to intervene more effectively in political debates. How can we use the knowledge that we already have to heal the imagined whole while keeping people in synchrony with each other and with the world they aspire to create for themselves and others?

The economic systems that sustain modern life have produced pernicious waste cultures. Globalization has accelerated planetary degradation and global warming through the continuous release of toxic waste. Every day, like millions of others, I dutifully clean and prepare my waste for recycling. I know it is no more than a transitory measure geared to grant manufacturers time to adjust and adapt. Reports that most waste will not be recycled, but dumped or burned, upset me deeply. How can anthropology remain a critical project in the face of such orchestrated cynicism, bad faith and indifference? How should anthropologists deploy their skills and bring a sense of shared responsibility to the task of replenishing the collective will?

To help to find answers to these questions, anthropologists need to radically rethink the ways in which we describe the processes and relations that tie communities to their environments. The extinction of experience (loss of direct contact with nature) that humankind currently suffers is massive, but not irreversible. New forms of storytelling have successfully challenged modernist myths, particularly their homophonic promises 7 . But there remain persistent challenges, such as the seductive and rampant power of one-size-fits-all progress, and the actions of elites, who thrive on emulation, and in doing so fuel run-away consumerism.

To combat these challenges, I simply reassert that ‘nature’ is far from having outlasted its historical utility. Anthropologists must join forces and reanimate their common exploration of the immense possibilities contained in human bodies and minds. No matter how overlooked or marginalized, these natural potentials hold the key to what keeps life going.

Laura M. Rival is Professor of Anthropology of Nature, Society and Development, ODID and SAME, University of Oxford, Oxford, UK .

Communication and media studies

Jean Burgess

The communication and media studies field has historically been animated by technological change. In the process, it has needed to navigate fundamental tensions: communication can be understood as both transmission (of information), and as (social) ritual 8 ; relatedly, media can be understood as both technology and as culture 9 .

The most important technological change over the past decade has been the ‘platformization’ 10 of the media environment. Large digital platforms owned by the world’s most powerful technology companies have come to have an outsized and transformative role in the transmission (distribution) of information, and in mediating social practices (whether major events or intimate daily routines). In response, digital methods have transformed the field. For example, advances in computational techniques enabled researchers to study patterns of communication on social media, leading to disciplinary trends such as the quantitative description of ‘hashtag publics’ in the mid-2010s 11 .

Platforms’ uses of data, algorithms and automation for personalization, content moderation and governance constitute a further major shift, giving rise to new methods (such as algorithmic audits) that go well beyond quantitative description 12 . But platform companies have had a patchy — at times hostile — relationship to independent research into their societal role, leading to data lockouts and even public attacks on researchers. It is important in the interests of public oversight and open science that we coordinate responses to such attempts to suppress research 13 , 14 .

As these processes of digital transformation continue, new connections between the humanities and technical disciplines will be necessary, giving rise to a new wave of methodological innovation. This next phase will also require more hybrid (qualitative and quantitative; computational and critical) methods 15 , not only to get around platform lockouts but also to ensure more careful attention is paid to how the new media technologies are used and experienced in everyday life. Here, innovative approaches such as the use of data donations can both aid the ‘platform observability’ 16 that is essential to accountability, and ensure that our research involves the perspectives of diverse audiences.

Jean Burgess is Professor of Digital Media at the School of Communication and Digital Media Research Centre (DMRC), Queensland University of Technology, Brisbane, Queensland Australia; and Associate Director at the Australian Research Council Centre of Excellence for Automated Decision-Making and Society (ADM+S), Melbourne, Victoria, Australia .

Computational social science

Claudia Wagner

Computational social science has emerged as a discipline that leverages computational methods and new technologies to collect, model and analyse digital behavioural data in natural environments or in large-scale designed experiments, and combine them with other data sources (such as survey data).

While the community made critical progress in enhancing our understanding about empirical phenomena such as the spread of misinformation 17 and the role of algorithms in curating misinformation 18 , it has focused less on questions about the quality and accessibility of data, the validity, reliability and reusability of measurements, the potential consequences of measurements and the connection between data, measurement and theory.

I see the following opportunities to address these issues.

First, we need to establish privacy-preserving, shared data infrastructures that collect and triangulate survey data with scientifically motivated organic or designed observational data from diverse populations 19 . For example, longitudinal online panels in which participants allow researchers to track their web browsing behaviour and link these traces to their survey answers will not only facilitate substantive research on societal questions but also enable methodological research (for example, on the quality of different data sources and measurement models), and contribute to the reproducibility of computational social science research.

Second, best practices and scientific infrastructures are needed for supporting the development, evaluation and re-use of measurements and the critical reflection on potentially harmful consequences of measurements 20 . Social scientists have developed such best practices and infrastructural support for survey measurements to avoid using instruments for which the validity is unclear or even questionable, and to support the re-usability of survey scales. I believe that practices from survey methodology and other domains, such as the medical industry, can inform our thinking here.

Finally, the fusion of algorithmic and human behaviour invites us to rethink the various ways in which data, measurements and social theories can be connected 20 . For example, product recommendations that users receive are based on measurements of users’ interests and needs: however, users and measurements are not only influenced by those recommendations, but also influence them in turn. As a community we need to develop research designs and environments that help us to systematically enhance our understanding of those feedback loops.

Claudia Wagner is Head of Computational Social Science Department at GESIS – Leibniz Institute for the Social Sciences, Köln, Germany; Professor for Applied Computational Social Sciences at RWTH Aachen University, Aachen, Germany; and External Faculty Member of the Complexity Science Hub, Vienna, Austria .

Criminology

Daniel S. Nagin

Disciplinary silos in path-breaking science are disappearing. Criminology has had a longstanding tradition of interdisciplinarity, but mostly in the form of an uneasy truce of research from different disciplines appearing side-by-side in leading journals — a scholarly form of parallel play. In the future, this must change because the big unsolved challenges in criminology will require cooperation among all of the social and behavioural sciences.

These challenges include formally merging the macro-level themes emphasized by sociologists with the micro-, individual-level themes emphasized by psychologists and economists. Initial steps have been made by economists who apply game theory to model crime-relevant social interactions, but much remains to be done in building models that explain the formation and destruction of social trust, collective efficacy and norms, as they relate to legal definitions of criminal behaviour.

A second opportunity concerns the longstanding focus of criminology on crimes involving the physical taking of property and interpersonal physical violence. These crimes are still with us, but — as the daily news regularly reports — the internet has opened up broad new frontiers for crime that allow for thefts of property and identities at a distance, forms of extortion and human trafficking at a massive scale (often involving untraceable transactions using financial vehicles such as bitcoin) and interpersonal violence without physical contact. This is a new and largely unexplored frontier for criminological research that criminologists should dive into in collaboration with computer scientists who already are beginning to troll these virgin scholarly waters.

The final opportunity I will note also involves drawing from computer science, the primary home of what has come to be called machine learning. It is important that new generations of criminologists become proficient with machine learning methods and also collaborate with its creators. Machine learning and related statistical methods have wide applicability in both the traditional domains of criminological research and new frontiers. These include the use of prediction tools in criminal justice decision-making, which can aid in crime detection, and the prevention and measuring of crime both online and offline, but also have important implications for equity and fairness due to their consequential nature.

Daniel S. Nagin is Teresa and H. John Heinz III University Professor of Public Policy and Statistics at the Heinz College of Information Systems and Public Policy, Carnegie Mellon University, Pittsburgh, PA, USA .

Behavioural economics

Bertil Tungodden

Behavioural and experimental economics have transformed the field of economics by integrating irrationality and nonselfish motivation in the study of human behaviour and social interaction. A richer foundation of human behaviour has opened many new exciting research avenues, and I here highlight three that I find particularly promising.

Economists have typically assumed that preferences are fixed and stable, but a growing literature, combining field and laboratory experimental approaches, has provided novel evidence on how the social environment shapes our moral and selfish preferences. It has been shown that prosocial role models make people less selfish 21 , that early-childhood education affects the fairness views of children 22 and that grit can be fostered in the correct classroom environment 23 . Such insights are important for understanding how exposure to different institutions and socialization processes influence the intergenerational transmission of preferences, but much more work is needed to gain systematic and robust evidence on the malleability of the many dimensions that shape human behaviour.

The moral mind is an important determinant of human behaviour, but our understanding of the complexity of moral motivation is still in its infancy. A growing literature, using an impartial spectator design in which study participants make consequential choices for others, has shown that people often disagree on what is morally acceptable. An important example is how people differ in their view of what is a fair inequality, ranging from the libertarian fairness view to the strict egalitarian fairness view 24 , 25 . An exciting question for future research is whether such moral differences reflect a concern for other moral values, such as freedom, or irrational considerations.

A third exciting development in behavioural and experimental economics is the growing set of global studies on the foundations of human behaviour 26 , 27 . It speaks to the major concern in the social sciences that our evidence is unrepresentative and largely based on studies with samples from Western, educated, industrialized, rich and democratic societies 28 . The increased availability of infrastructure for implementing large-scale experimental data collections and methodological advances carry promise that behavioural and experimental economic research will broaden our understanding of the foundations of human behaviour in the coming years.

Bertil Tungodden is Professor and Scientific Director of the Centre of Excellence FAIR at NHH Norwegian School of Economics, Bergen, Norway .

Development economics

Esther Duflo

The past three decades have been a wonderful time for development economics. The number of scholars, the number of publications and the visibility of the work has dramatically increased. Development economists think about education, health, firm growth, mental health, climate, democratic rules and much more. No topic seems off limits!

This progress is intimately connected with the explosion of the use of randomized controlled trials (RCTs) and, more generally, with the embrace of careful causal identification. RCTs have markedly transformed development economics and made it the field that it is today.

The past three decades (until the COVID-19 crisis) have also been very good for improving the circumstances of low-income people around the world: poverty rates have fallen; school enrolment has increased; and maternal and infant mortality has been halved. Although I would not dare imply that the two trends are causally related, one of the reasons for these improvements in the quality of life — even in countries where economic growth has been slow — is the greater focus on pragmatic solutions to the fundamental problems faced by people with few resources. In many countries, development economics researchers (particularly those working with RCTs) have been closely involved with policy-makers, helping them to develop, implement and test these solutions. In turn, this involvement has been a fertile ground for new questions, which have enriched the field.

I imagine future change will, once again, come from an unexpected place. One possible driver of innovation will come from this meeting between the requirements of policy and the intellectual ambition of researchers. This means that the new challenges of our planet must (and will) become the new challenges of development economics. Those challenges are, I believe, quite clear: rethinking social protection to be better prepared to face risks such as the COVID-19 pandemic; mitigating, but unfortunately also adapting to, climate changes; curbing pollution; and addressing gender, racial and ethnic inequality.

To address these critical issues, I believe the field will continue to rely on RCTs, but also start using more creatively (descriptively or in combination with RCTs) the huge amount of data that is increasingly available as governments, even in poor countries, digitize their operations. I cannot wait to be surprised by what comes next.

Esther Duflo is The Abdul Latif Jameel Professor of Poverty Alleviation and Development Economics at the Department of Economics, Massachusetts Institute of Technology, Cambridge MA, USA; and cofounder and codirector of the Abdul Latif Jameel Poverty Action Lab (J-PAL) .

Political science

Janet M. Box-Steffensmeier

Political science remains one of the most pluralistic disciplines and we are on the move towards engaged pluralism. This takes us beyond mere tolerance to true, sincere engagement across methods, methodologies, theories and even disciplinary boundaries. Engaged pluralism means doing the hard work of understanding our own research from the multiple perspectives of others.

More data are being collected on human behaviour than ever before and our advances in methods better address the inherent interdependencies of the data across time, space and context. There are new ways to measure human behaviour via text, image and video. Data creation can even go back in time. All these advancements bode well for the potential to better understand and predict behaviour. This ‘data century’ and ‘golden age of methods’ also hold the promise to bridge, not divide, political science, provided that there is engaged methodological pluralism. Qualitative methods provide unique insights and perspectives when joined with quantitative methods, as does a broader conception of the methodologies underlying and launching our research.

I remain a strong proponent of leveraging dynamics and focusing on heterogeneity in our research questions to advance our disciplines. Doing so brings in an explicit perspective of comparison around similarity and difference. Our questions, hypotheses and theories are often made more compelling when considering the dynamics and heterogeneity that emerges when thinking about time and change.

Striving for a better understanding of gender, race and ethnicity is driving deeper and fuller understandings of central questions in the social sciences. The diversity of the research teams themselves across gender, sex, race, ethnicity, first-generation status, religion, ideology, partisanship and cultures also pushes advancement. One area that we need to better support is career diversity. Supporting careers in government, non-profit organizations and industry, as well as academia, for graduate students will enhance our disciplines and accelerate the production of knowledge that changes the world.

Engaged pluralism remains a foundational key to advancement in political science. Engaged pluralism supports critical diversity, equity and inclusion work, strengthens political scientists’ commitment to democratic principles, and encourages civic engagement more broadly. It is an exciting time to be a social scientist.

Janet M. Box-Steffensmeier is Vernal Riffe Professor of Political Science, Professor of Sociology (courtesy) and Distinguished University Professor at the Department of Political Science, Ohio State University, Columbus OH, USA; and immediate past President of the American Political Science Association .

Cognitive psychology

Andrew Perfors

Cognitive psychology excels at understanding questions whose problem-space is well-defined, with precisely specified theories that transparently map onto thoroughly explored experimental paradigms. That means there is a vast gulf between the current state of the art and the richness and complexity of cognition in the real world. The most exciting open questions are about how to bridge that gap without sacrificing rigour and precision. This requires at least three changes.

First, we must move beyond typical experiments. Stimuli must become less artificial, with a naturalistic structure and distribution. Similarly, tasks must become more ecologically valid: less isolated, with more uncertainty, embedded in natural situations and over different time-scales.

Second, we must move beyond considering individuals in isolation. We live in a rich social world and an environment that is heavily shaped by other humans. How we think, learn and act is deeply affected by how other people think and interact with us; cognitive science needs to engage with this more.

Third, we must move beyond the metaphor of humans as computers. Our cognition is deeply intertwined with our emotions, motivations and senses. These are more than just parameters in our minds; they have a complexity and logic of their own, and interact in nontrivial ways with each other and more typical cognitive domains such as learning, reasoning and acting.

How do we make progress on these steps? We need reliable real-world data that are comparable across people and situations, reflect the cognitive processes involved and are not changed by measurement. Technology may help us with this, but challenges surrounding privacy and data quality are huge. Our models and analytic approaches must also grow in complexity — commensurate with the growth in problem and data complexity — without becoming intractable or losing their explanatory power.

Success in this endeavour calls for a different kind of science that is not centred around individual laboratories or small stand-alone projects. The biggest advances will be achieved on the basis of large, rich, real-world datasets from different populations, created and analysed in collaborative teams that span multiple domains, fields and approaches. This requires incentive structures that reward team-focused, slower science and prioritize the systematic construction of reliable knowledge over splashy findings.

Andrew Perfors is Associate Professor and Deputy Director of the Complex Human Data Hub, University of Melbourne, Melbourne, Victoria, Australia .

Cultural and social psychology

Ying-yi Hong

I am writing this at an exceptional moment in human history. For two years, the world has faced the COVID-19 pandemic and there is no end in sight. Cultural and social psychology are uniquely equipped to understand the COVID-19 pandemic, specifically examining how people, communities and countries are dealing with this extreme global crisis — especially at a time when many parts of the world are already experiencing geopolitical upheaval.

During the pandemic, and across different nations and regions, a diverse set of strategies (and subsequent levels of effectiveness) were used to curb the spread of the disease. In the first year of the pandemic, research revealed that some cultural worldviews — such as collectivism (versus individualism) and tight (versus loose) norms — were positively associated with compliance with COVID-19 preventive measures as well as with fewer infections and deaths 29 , 30 . These worldview differences arguably stem from different perspectives on abiding to social norms and prioritizing the collective welfare over an individual’s autonomy and liberty. Although in the short term it seems that a collectivist or tight worldview has been advantageous, it is unclear whether this will remain the case in the long term. Cultural worldviews are ‘tools’ that individuals use to decipher the meaning of their environment, and are dynamic rather than static 31 . Future research can examine how cultural worldviews and global threats co-evolve.

The pandemic has also amplified the demarcation of national, political and other major social categories. On the one hand, identification with some groups (for example, national identity) was found to increase in-group care and thus a greater willingness to sacrifice personal autonomy to comply with COVID-19 measures 32 . On the other hand, identification with other groups (for example, political parties) widened the ideological divide between groups and drove opposing behaviours towards COVID-19 measures and health outcomes 33 . As we are facing climate change and other pressing global challenges, understanding the role of social identities and how they affect worldviews, cognition and behaviour will be vital. How can we foster more inclusive (versus exclusive) identities that can unite rather than divide people and nations?

Ying-yi Hong is Choh-Ming Li Professor of Management and Associate Dean (Research) at the Department of Management, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China .

Developmental psychology

Alison Gopnik

Developmental psychology is similar to the kind of book or band that, paradoxically, everyone agrees is underrated. On the one hand, children and the people who care for them are often undervalued and overlooked. On the other, since Piaget, developmental research has tackled some of the most profound philosophical questions about every kind of human behaviour. This will only continue into the future.

Psychologists increasingly recognize that the minds of children are not just a waystation or an incomplete version of adult minds. Instead, childhood is a distinct evolutionarily adaptive phase of an organism, with its own characteristic cognitions, emotions and motivations. These characteristics of childhood reflect a different agenda than those of the adult mind — a drive to explore rather than exploit. This drive comes with motivations such as curiosity, emotions such as wonder and surprise and remarkable cognitive learning capacities. A new flood of research on curiosity, for example, shows that children actively seek out the information that will help them to learn the most.

The example of curiosity also reflects the exciting prospects for interdisciplinary developmental science. Machine learning is increasingly using children’s learning as a model, and developmental psychologists are developing more precise models as a result. Curiosity-based AI can illuminate both human and machine intelligence. Collaborations with biology are also exciting: for example, in work on evolutionary ‘life history’ explanations of the effects of adverse experiences on later life, and new research on plasticity and sensitive periods in neuroscience. Finally, children are at the cutting edge of culture, and developmental psychologists increasingly conduct a much wider range of cross-cultural studies.

But perhaps the most important development is that policy-makers are finally starting to realize just how crucial children are to important social issues. Developmental science has shown that providing children with the care that they need can decrease poverty, inequality, disease and violence. But that care has been largely invisible to policy-makers and politicians. Understanding scientifically how caregiving works and how to support it more effectively will be the most important challenge for developmental psychology in the next century.

Alison Gopnik is Professor of Psychology and Affiliate Professor of Philosophy at the Department of Psychology, University of California at Berkeley, Berkeley, CA, USA .

Science of science

Cassidy R. Sugimoto

Why study science? The goal of science is to advance knowledge to improve the human condition. It is, therefore, essential that we understand how science operates to maximize efficiency and social good. The metasciences are fields that are devoted to understanding the scientific enterprise. These fields are distinguished by differing epistemologies embedded in their names: the philosophy, history and sociology of science represent canonical metasciences that use theories and methods from their mother disciplines. The ‘science of science’ uses empirical approaches to understand the mechanisms of science. As mid-twentieth-century science historian Derek de Solla Price observed, science of science allows us to “turn the tools of science on science itself” 34 .

Contemporary questions in the science of science investigate, inter alia, catalysts of discovery and innovation, consequences of increased access to scientific information, role of teams in knowledge creation and the implications of social stratification on the scientific enterprise. Investigation of these issues require triangulation of data and integration across the metasciences, to generate robust theories, model on valid assumptions and interpret results appropriately. Community-owned infrastructure and collective venues for communication are essential to achieve these goals. The construction of large-scale science observatories, for example, would provide an opportunity to capture the rapidly expanding dataverse, collaborate and share data, and provide nimble translations of data into information for policy-makers and the scientific community.

The topical foci of the field are also undergoing rapid transformation. The expansion of datasets enables researchers to analyse a fuller population, rather than a narrow sample that favours particular communities. The field has moved from an elitist focus on ‘success’ and ‘impact’ to a more-inclusive and prosopographical perspective. Conversations have shifted from citations, impact factors and h -indices towards responsible indicators, diversity and broader impacts. Instead of asking ‘how can we predict the next Nobel prize winner?’, we can ask ‘what are the consequences of attrition in the scientific workforce?’. The turn towards contextualized measurements that use more inclusive datasets to understand the entire system of science places the science of science in a ripe position to inform policy and propel us towards a more innovative and equitable future.

Cassidy R. Sugimoto is Professor and Tom and Marie Patton School Chair, School of Public Policy, Georgia Institute of Technology, Atlanta, GA, USA .

Sari Hanafi

In the past few years, we have been living through times in which reasonable debate has become impossible. Demagogical times are driven by the vertiginous rise of populism and authoritarianism, which we saw in the triumph of Donald Trump in the USA and numerous other populist or authoritarian leaders in many places around the globe. There are some pressing tasks for sociology that can be, in brief, reduced to three.

First, fostering democracy and the democratization process requires disentangling the constitutive values that compose the liberal political project (personal liberty, equality, moral autonomy and multiculturalism) to address the question of social justice and to accommodate the surge in people’s religiosity in many parts in the globe.

Second, the struggle for the environment is inseparable from our choice of political economy, and from the nature of our desired economic system — and these connections between human beings and nature have never been as intimate as they are now. Past decades saw rapid growth that was based on assumptions of the long-term stability of the fixed costs of raw materials and energy. But this is no longer the case. More recently, financial speculation intensified and profits shrunk, generating distributional conflicts between workers, management, owners and tax authorities. The nature of our economic system is now in acute crisis.

The answer lies in a consciously slow-growing new economy that incorporates the biophysical foundations of economics into its functioning mechanisms. Society and nature cannot continue to be perceived each as differentiated into separate compartments. The spheres of nature, culture, politics, social, economy and religion are indeed traversed by common logics that allow a given society to be encompassed in its totality, exactly as Marcel Mauss 35 did. The logic of power and interests embodied in ‘ Homo economicus ’ prevents us from being able to see the potentiality of human beings to cultivate gift-giving practices as an anthropological foundation innate within social relationships.

Third, there are serious social effects of digitalized forms of labour and the trend of replacing labour with an automaton. Even if digital labour partially reduces the unemployment rate, the lack of social protection for digital labourers would have tremendous effects on future generations.

In brief, it is time to connect sociology to moral and political philosophy to address fundamentally post-COVID-19 challenges.

Sari Hanafi is Professor of Sociology at the American University of Beirut, Beirut, Lebanon; and President of the International Sociological Association .

Environmental studies (climate change)

Yasuko Kameyama

Climate change has been discussed for more than 40 years as a multilateral issue that poses a great threat to humankind and ecosystems. Unfortunately, we are still talking about the same issue today. Why can’t we solve this problem, even though scientists pointed out its importance and urgency so many years ago?

These past years have been spent trying to prove the causal relationship between an increase in greenhouse gas concentrations, global temperature rise and various extreme weather events, as well as developing and disseminating technologies needed to reduce emissions. All of these tasks have been handled by experts in the field. At the same time, the general public invested little time in this movement, probably expecting that the problem would be solved by experts and policy-makers. But that has not been the case. No matter how much scientists have emphasized the crisis of climate change or how many clean energy technologies engineers have developed, society has resisted making the necessary changes. Now, the chances of keeping the temperature rise within 1.5 °C of pre-industrial levels — the goal necessary to minimize the effects of climate change — are diminishing.

We seem to finally be realizing the importance of social scientific knowledge. People need to take scientific information seriously for clean technology to be quickly diffused. Companies are more interested in investing in newer technology and product development when they know that their products will sell. Because environmental problems are caused by human activity, research on human behaviour is indispensable in solving these problems.

Reports by the Intergovernmental Panel on Climate Change (IPCC) have not devoted many pages to the areas of human awareness and behaviour ( https://www.ipcc.ch/ ). The IPCC’s Third Working Group, which deals with mitigation measures, has partially spotlighted research on institutions, as well as on concepts such as fairness. People’s perception of climate change and the relationship between perception and behavioural change differ depending on the country, societal structure and culture. Additional studies in these areas are required and, for that purpose, more studies from regions such as Asia, Africa and South America, which are underrepresented in terms of the number of academic publications, are particularly needed.

Yasuko Kameyama is Director, Social Systems Division, National Institute for Environmental Studies, Tsukuba, Japan .

Sustainability (food systems)

Mario Herrero

The food system is in dire straits. Food demand is unprecedented, while malnutrition in all its forms (obesity, undernutrition and micronutrient deficiencies) is rampant. Environmental degradation is pervasive and increasing, and if it continues, the comfort zone for humanity and ecosystems to thrive will be seriously compromised. From bruises and shapes to sell-by dates, we tend to find many reasons to exclude perfectly edible food from our plates, whereas in other cases not enough food reaches hungry mouths owing to farming methods, pests and lack of adequate storage. These types of inequalities are common and — together with inherent perverse incentives that maintain the status quo of how we produce, consume and waste increasingly cheap and processed food — they are launching us towards a disaster.

We are banking on a substantial transformation of the food system to solve this conundrum. Modifying food consumption and waste patterns are central to the plan for achieving healthier diets, while increasing the sustainability of our food system. This is also an attractive policy proposition, as it could lead to gains in several sectors. Noncommunicable diseases such as obesity, diabetes and heart disease could decline, while reducing the effects of climate change, deforestation, excessive water withdrawals and biodiversity loss, and their enormous associated — and largely unaccounted — costs.

Modifying our food consumption and waste patterns is very hard, and unfortunately we know very little about how to change them at scale. Yes, many pilots and small examples exist on pricing, procurement, food environments and others, but the evidence is scarce, and the magnitude of the change required demands an unprecedented transdisciplinary research agenda. The problem is at the centre of human agency and behaviour, embodying culture, habits, values, social status, economics and all aspects of agri-food systems. Certainly, one of the big research areas for the next decade if we are to reach the Sustainable Development Goals leaving no one behind.

Mario Herrero is Professor, Cornell Atkinson scholar and Nancy and Peter Meinig Family Investigator in the Life Sciences at the Department of Global Development, College of Agriculture and Life Sciences and Cornell Atkinson Center for Sustainability, Cornell University, Ithaca, NY, USA .

Cultural evolution

Laurel Fogarty

Humans are the ultimate ‘cultural animals’. We are innovative, pass our cultures to one another across generations and build vast self-constructed environments that reflect our cultural biases. We achieve things using our cultural capacities that are unimaginable for any other species on earth. And yet we have only begun to understand the dynamics of cultural change, the drivers of cultural complexity or the ways that we adapt culturally to changing environments. Scholars — anthropologists, archaeologists and sociologists — have long studied culture, aiming to describe and understand its staggering diversity. The relatively new field of cultural evolution has different aims, one of the most important of which is to understand the mechanics in the background — what general principles, if any, govern human cultural change?

Although the analogy of culture as an evolutionary process has been made since at least the time of Darwin 36 , 37 , cultural evolution as a robust field of study is much younger. From its beginnings with the pioneering work of Cavalli-Sforza & Feldman 38 , 39 , 40 and Boyd & Richerson 41 , 42 , the field of cultural evolution has been heavily theoretical. It has drawn on models from genetic evolution 40 , 43 , 44 , 45 , ecology 46 , 47 and epidemiology 40 , 48 , extending and adapting them to account for unique and important aspects of cultural transmission. Indeed, in its short life, the field of cultural evolution has largely been dominated by a growing body of theory that ensured that the fledgling field started out on solid foundations. Because it underpins and makes possible novel applications of cultural evolutionary ideas, theoretical cultural evolution’s continued development is not only crucial to the field’s growth but also represents some of its most exciting future work.

One of the most urgent tasks for cultural evolution researchers in the next five years is to develop, alongside its theoretical foundations, robust principles of application 49 , 50 , 51 . In other words, it is vital to develop our understanding of what we can — and, crucially, cannot — infer from different types of cultural data. Where do we draw those boundaries and how can we apply cultural evolutionary theory to cultural datasets in a principled way? The tandem development of robust theory and principled application has the potential to strengthen cultural evolution as a robust, useful and ground-breaking inferential science of human behaviour.

Laurel Fogarty is Senior Scientist at the Department of Human Behaviour, Ecology, and Culture, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany .

Over the past decade, research using molecular genetic data has confirmed one of the main conclusions of twin studies: all human behaviour is partly heritable 52 , 53 . Attempts at examining the link between genetics and behaviour have been met with concerns that the findings can be abused to justify discrimination — and there are good historical grounds for these concerns. However, these findings also show that ignoring the contribution of genes to variation in human behaviour could be detrimental to a complete understanding of social phenomena, given the complex ways that genes and environment interact.

Uncovering these complex pathways has become feasible only recently thanks to rapid technological progress reducing the costs of genotyping. Sample sizes in genome-wide association studies (GWAS) have risen from tens of thousands to millions in the past decade, reporting thousands of genetic variants associated with different behaviours 54 , 55 , 56 , 57 . New ways to use GWAS results have emerged, the most important one arguably being a method to aggregate the additive effects of many genetic variants into a ‘polygenic index’ (PGI) (also known as a ‘polygenic score’) that summarizes an individual’s genetic propensity towards a trait or behaviour 58 , 59 . Being aggregate measures, PGIs capture a much larger share of the variance in the trait of interest compared to individual genetic variants 60 . Thus, they have paved the way for follow-up studies with smaller sample sizes but deeper phenotyping compared to the original GWAS, allowing researchers to, for example, analyse the channels through which genes operate 61 , 62 , how they interact with the environment 63 , 64 , and account for confounding bias and boost statistical power by controlling for genetic effects 65 , 66 .

Useful as they are, PGIs and the GWAS that they are based on can suffer from confounding due to environmental factors that correlate with genotypes, such as population stratification, indirect effect from relatives or assortative mating 67 . Now that the availability of genetic data enables large-scale within-family GWAS, the next big thing in behaviour genetic research will be disentangling these sources 68 . While carrying the progress further, it is important that the field prioritizes moving away from its currently predominant Eurocentric bias by extending data collection and analyses to individuals of non-European ancestries, as the exclusion of non-European ancestries from genetic research has the potential to exacerbate health disparities 69 . Researchers should also be careful to communicate their findings clearly and responsibly to the public and guard against their misappropriation by attempts to fuel discriminatory action and discourse 70 .

Aysu Okbay is Assistant Professor at the Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands .

Cognitive neuroscience

Anna C. Nobre

Since the ‘decade of the brain’ in the 1990s, ingenuity in cognitive neuroscience has focused on measuring and analysing brain signals. Adapting tools from statistics, engineering, computer science, physics and other disciplines, we studied activity, states, connectivity, interactions, time courses and dynamics in brain regions and networks. Unexpected findings about the brain yielded important insights about the mind.

Now is a propitious time to upgrade the brain–mind duumvirate to a brain–mind–behaviour triumvirate. Brain and mind are embodied, and their workings are expressed through various effectors. Yet, experimental tasks typically use simple responses to capture complex psychological functions. Often, a button press — with its limited dimensions of latency and accuracy — measures anticipating, focusing, evaluating, choosing, reflecting or remembering. Researchers venturing beyond such simple responses are uncovering how the contents of mind can be studied using various continuous measures, such as pupil diameter, gaze shifts and movement trajectories.

Most tasks also restrict participants’ movements to ensure experimental control. However, we are learning that principles of cognition derived in artificial laboratory contexts can fail to generalize to natural behaviour. Virtual reality should prove a powerful methodology. Participants can behave naturally, and experimenters can control stimulation and obtain quality measures of gaze, hand and body movements. Noninvasive neurophysiology methods are becoming increasingly portable. Exciting immersive brain–mind–behaviour studies are just ahead.

The next necessary step is out of the academic bubble. Today the richest data on human behaviour belong to the information and technology industries. In our routines, we contribute data streams through telephones, keyboards, watches, vehicles and countless smart devices in the internet of things. These expose properties such as processing speed, fluency, attention, dexterity, navigation and social context. We supplement these by broadcasting feelings, attitudes and opinions through social media and other forums. The richness and scale of the resulting big data offer unprecedented opportunities for deriving predictive patterns that are relevant to understanding human cognition (and its disorders). The outcomes can then guide further hypothesis-driven experimentation. Cognitive neuroscience is intrinsically collaborative, combining a broad spectrum of disciplines to study the mind. Its challenge now is to move from a multidisciplinary to a multi-enterprise science.

Anna C. Nobre is Chair in Translational Cognitive Neuroscience at the Department of Experimental Psychology, University of Oxford, UK; and Director of Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, UK .

Social and affective neuroscience

Tatia M. C. Lee

Social and affective neuroscience is a relatively new, but rapidly developing, field of neuroscience. Social and affective neuroscience research takes a multilevel approach to make sense of socioaffective processes, focusing on macro- (for example, social environments and structures), meso- (for example, social interactions) and micro (for example, socio-affective neural processes and perceptions)-level interactions. Because the products of these interactions are person-specific, the conventional application of group-averaged mechanisms to understand the brain in a socioemotional context has been reconsidered. Researchers turn to ecologically valid stimuli (for example, dynamic and virtual reality instead of static stimuli) and experimental settings (for example, real-time social interaction) 71 to address interindividual differences in social and affective responses. At the neural level, there has been a shift of research focus from local neural activations to large-scale synchronized interactions across neural networks. Network science contributes to the understanding of dynamic changes of neural processes that reflect the interactions and interconnection of neural structures that underpin social and affective processes.

We are living in an ever-changing socioaffective world, full of unexpected challenges. The ageing population and an increasing prevalence of depression are social phenomena on a global scale. Social isolation and loneliness caused by measures to tackle the current pandemic affect physical and psychological well-being of people from all walks of life. These global issues require timely research efforts to generate potential solutions. In this regard, social and affective neuroscience research using computational modelling, longitudinal research designs and multimodal data integration will create knowledge about the basis of adaptive and maladaptive social and affective neurobehavioural processes and responses 72 , 73 , 74 . Such knowledge offers important insights into the precise delineation of brain–symptom relationships, and hence the development of prediction models of cognitive and socioaffective functioning (for example, refs. 75 , 76 ). Therefore, screening tools for identifying potential vulnerabilities can be developed, and timely and precise interventions can be tailored to meet individual situations and needs. The translational application of social and affective neuroscience research to precision medicine (and policy) is experiencing unprecedented demand, and such demand is met with unprecedented clinical and research capabilities.

Tatia M. C. Lee is Chair Professor of Psychology at the State Key Laboratory of Brain and Cognitive Sciences and Laboratory of Neuropsychology and Human Neuroscience, The University of Hong Kong, Hong Kong Special Administrative Region, China .

Maurizio Corbetta

Focal brain disorders, including stroke, trauma and epilepsy, are the main causes of disability and loss of productivity in the world, and carry a cumulative cost in Europe of about € 500 billion per year 77 . The disease process affects a specific circuit in the brain by turning it off (as in stroke) or pathologically turning it on (as in epilepsy). The cause of the disabling symptoms is typically local circuit damage. However, there is now overwhelming evidence that symptoms reflect not only local pathology but also widespread (network) functional abnormalities. For instance, in stroke, an average lesion — the size of a golf ball — typically alters the activity of on average 25% of all brain connections. Furthermore, normalization of these abnormalities correlates with optimal recovery of function 78 , 79 .

One exciting treatment opportunity is ‘circuit-based’ stimulation: an ensemble of methods (optogenetic, photoacoustic, electrochemical, magnetic and electrical) that have the potential to normalize activity. Presently, this type of therapy is limited by numerous factors, including a lack of knowledge about the circuits, the difficulty of mapping these circuits in single patients and, most importantly, a principled understanding of where and how to stimulate to produce functional recovery.

A possible solution lies in a strategy (developed with G. Deco, M. Massimini and M. Sanchez-Vivez) that starts with an in-depth assessment of behaviour and physiological studies of brain activity to characterize the affected circuits and associated patterns of functional abnormalities. Such a multi-dimensional physiological map of a lesioned brain can be then fed to biologically realistic in silico models 80 . A model of a lesioned brain affords the opportunity to explore, in an exhaustive way, different kinds of stimulation to normalize faulty activity. Once a suitable protocol is found it can be exported first to animal models, and then to humans. Stimulation alone will not be enough. Pairing with behavioural training (rehabilitation) will stabilize learning and normalize connections.

The ability to interface therapy (stimulation, rehabilitation and drugs) with brain signals or other kinds of behavioural sensor offers another exciting opportunity, to open the ‘brain’s black box’. Most current treatments in neuroscience are given with no regard to their effect on the underlying brain signals or behaviour. Giving patients conscious access to their own brain signals may substantially enhance recovery, as the brain is now in the position to use its own powerful connections and learning mechanisms to cure itself.

Maurizio Corbetta is Professor and Chair of Neurology at the Department of Neuroscience and Director of the Padova Neuroscience Center (PNC), University of Padova, Italy; and Principal Investigator at the Venetian Institute of Molecular Medicine (VIMM), Padova, Italy .

Merete Nordentoft

Schizophrenia and related psychotic disorders are among the costliest and most debilitating disorders in terms of personal sufferings for those affected, for relatives and for society 81 . These disorders often require long-term treatment and, for a substantial proportion of the patients, the outcomes are poor. This has motivated efforts to prevent long-lasting illness by early intervention. The time around the onset of psychotic disorders is associated with an increased risk of suicide, of loss of affiliation with the labour market, and social isolation and exclusion. Therefore, prevention and treatment of first-episode psychosis will be a key challenge for the future.

There is now solid evidence proving that early intervention services can improve clinical outcomes 82 . This was first demonstrated in the large Danish OPUS trial, in which OPUS treatment — consisting of assertive outreach, case management and family involvement, provided by multidisciplinary teams over a two-year period — was shown to improve clinical outcomes 83 . Moreover, it was also cost-effective 84 . Although the positive effects on clinical outcomes were not sustainable after five and ten years, there was a long-lasting effect on use of supported housing facilities (indicating improved ability to live independently) 85 . Later trials proved that it is possible to maintain the positive clinical outcomes by extending the services to five years or by offering a stepped care model with continued intensive care for the patients who are most impaired 86 . However, even though both clinical and functional outcomes (such as labour market affiliation) can be improved by evidence-based treatments 82 , a large group of patients with first-episode psychosis still have psychotic symptoms after ten years. Thus, there is still an urgent need for identification of new and better options for treatment.

Most probably, some of the disease processes start long before first onset of a psychotic disorder. Thus, identifying disease mechanisms and possibilities for intervention before onset of psychosis will be extremely valuable. Evidence for effective preventive interventions is very limited, and the most burning question — of how to prevent psychosis — is still open.

The early intervention approach is also promising also for other disorders, including bipolar affective disorder, depression, anxiety, eating disorders, personality disorders, autism and attention-deficient hyperactivity disorder.

Merete Nordentoft is Clinical Professor at the Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark; and Principal Investigator, CORE - Copenhagen Research Centre for Mental Health, Mental Health Centre Copenhagen, Copenhagen University Hospital, Copenhagen, Denmark .

Epidemiology

Gabriel M. Leung

In a widely anthologized article from the business field of marketing, Levitt 87 pointed out that often industries failed to grow because they suffered from a limited market view. For example, Kodak went bust because it narrowly defined itself as a film camera company for still photography rather than one that should have been about imaging writ large. If it had had that strategic insight, it would have exploited and invested in digital technologies aggressively and perhaps gone down the rather more successful path of Fujifilm — or even developed into territory now cornered by Netflix.

The raison d’être of epidemiology has been to provide a set of robust scientific methods that underpin public health practice. In turn, the field of public health has expanded to fulfil the much-wider and more-intensive demands of protecting, maintaining and promoting the health of local and global populations, intergenerationally. At its broadest, the mission of public health should be to advance social justice towards a complete state of health.

Therefore, epidemiologists should continue to recruit and embrace relevant methodology sets that could answer public health questions, better and more efficiently. For instance, Davey Smith and Ebrahim 88 described how epidemiology adapted instrumental variable analysis that had been widely deployed in econometrics to fundamentally improve causal inference in observational epidemiology. Conversely, economists have not been shy in adopting the randomized controlled trial design to answer questions of development, and have recognized it with a Nobel prize 89 . COVID-19 has brought mathematical epidemiology or modelling to the fore. The foundations of the field borrowed heavily from population dynamics and ecological theory.

In future, classical epidemiology, which has mostly focused on studying how the exposome associates with the phenome, needs to take into simultaneous account the other layers of the multiomics universe — from the genome to the metabolome to the microbiome 90 . Another area requiring innovative thinking concerns how to harness big data to better understand human behaviour 91 . Finally, we must consider key questions that are amenable to epidemiologic investigation arising from the major global health challenges: climate change, harmful addictions and mental wellness. What new methodological tools do we need to answer these questions?

Epidemiologists must keep trying on new lenses that correct our own siloed myopia.

Gabriel M. Leung is Helen and Francis Zimmern Professor in Population Health at WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, LKS Faculty of Medicine, The University of Hong Kong; Chief Scientific Officer at Laboratory of Data Discovery for Health, Hong Kong Science and Technology Park; and Dean of Medicine at the University of Hong Kong, Hong Kong Special Administrative Region, China .

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Box-Steffensmeier, J.M., Burgess, J., Corbetta, M. et al. The future of human behaviour research. Nat Hum Behav 6 , 15–24 (2022). https://doi.org/10.1038/s41562-021-01275-6

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Ireland’s youngest female councillor graduates from University of Limerick

Newly elected Clare County Councillor, Rachel Hartigan credits her success to working twice as hard as the average candidate, as she graduated from University of Limerick today (Thursday) with a Bachelor of Arts in European Studies . 

Aged 22, Cllr Hartigan might be the youngest female councillor in the country, but she is no stranger to politics, having studied it in UL, been an active member of Ógra Fianna Fáil, and interned for Clare TD Cathal Crowe. 

It was during her summer internship with Deputy Crowe that Rachel first considered running in the local elections.  

“I never would have seen myself running for elected politics”, she explained, “but working in Cathal's office, a lot of the queries coming in were what I would imagine a local councillor should really be dealing with. 

“And that's when I realised I didn't know who my local councillor was, which seemed bizarre because I'm a politics student, interning in my TD's office, so I'm politically engaged.  

“And there's a lot that a local councillor deals with that has a huge impact on people's day-to-day lives, and I felt like we were really missing that strong voice.” 

Cllr Hartigan also credits a lack of representation amongst local councillors as a key factor that “spurred” her to action: “I think the median age of a councillor in Ireland is somewhere in the 70s bracket and I felt like that was extremely unfair. 

“When we look at why younger people don't come out in droves to vote a lot of the time, what stood out to me was we can't identify with our politicians. 

“We don't feel like they speak for us and they don't take the time to get to know what our issues are and what's important to us. 

“We're kind of written off and cast aside a lot of the time, and that really spurred me to action as well.” 

Rachel was one of more than 3,600 students to graduate at UL this week, and as a first-time local representative, she said her degree in European Studies has “without a doubt” helped to prepare her for her new role.  

“I could probably go through reams of actual content and papers and academic research that I did, I could give you exact examples that will come into play now in my role, but the main thing is critical thinking. It is the ability to be open minded and have the skills to do your own research, that is the biggest thing. 

“Because there is no guidebook, there is no induction to becoming a councillor, so I'm dealing with queries on housing, medical cards, roads, and footpaths, it's a broad range of issues and I've just started, so having the skills to be able to research properly and effectively and efficiently is huge and I genuinely wouldn't be able to do what I'm doing now had I not learned those really important research skills in UL. 

“Obviously studying politics comes into it but in terms of the other subjects I studied, my time studying marketing was hugely helpful, particularly in planning the campaign. 

“It was massively beneficial to have an understanding of consumer culture and behavior and being able to approach social media strategically, not just throwing something up for the sake of it. And they're all skills and habits that I picked up in my time as a student in UL.” 

Commenting on the landscape for a young woman running an election campaign, Cllr Hartigan said: “I did get a lot of ‘Oh you'll get elected because you're a woman, so you'll get the woman vote or you'll get elected because you're a young person.’ 

“I got elected because I worked my ass off, that's why I got elected.  

“There wasn't an army of young people or an army of women heading to the polling station for me, that's just not what happened, as much as that would have been really cool to see. 

“I got elected because I was canvassing for six or seven hours a day, I was on top of my social media, I was planning and hosting public meetings. 

“I was doing all of the things that you need to do to win, but I was working twice as hard as the average candidate because I had a lot to prove because I am a young woman, so it doesn't make it easier to run as a woman or a young person like some people suggest. 

“You actually have to prove yourself twice as much, and that's not fair, but I think the only way that that will change is if we get more women in and more young people in.” 

Cllr Hartigan credits the support of her family and lecturers in helping her throughout her election campaign.  

“My lecturer Dr Scott Fitzsimmons was very supportive, as was course director Dr Xosé Boan, who advised me to watch myself and my own mental health and well-being as well.  

“Sometimes you get these grand ideas and you're just all go, all the time and you forget to take the time to mind yourself, so I was really glad to have been told that.” 

Rachel does not hail from a political family, with her mother Rosaleen working as a medical secretary and her father Paul the Chief Information Officer for Electric Ireland Superhomes. However, that did not stop Paul from taking on the role of campaign manager.  

“We both learned together and he came out with me every single night, as did my mom. I could not have done it without them,” explained Rachel. 

“Obviously, the focus and the attention is on the candidate, but behind the scenes nobody does it alone, your family has to be on board.  

“It's a huge, massive team effort and for all the work that I was doing with my final year in UL and campaigning, they were out canvassing with me just as much, spending just as many hours at the doors.” 

A native of Parteen, Co. Clare, Rachel attended Parteen National School and now represents the Shannon Electoral Area.  

Reflecting on achieving the two major milestones of graduating university and winning her first election, she said it hasn’t fully sunk in yet. 

“I really felt like I was a campaign/Final Year Project robot, and it’s only the last few weeks I've had time to sit and process and reflect. 

“You never really look at your own accomplishments and achievements and say ‘oh my God, that was really good’. I think Irish people in particular, and women too, are really bad at giving themselves a pat on the back, even when it's well deserved. 

“I'm trying to take in the huge accomplishment, but it's hard to come out and say that and to even feel it, so that's something I'm working on at the moment, giving myself a little pat on the back.”