1st Edition

Handbook of Computational Social Science, Volume 1 Theory, Case Studies and Ethics

Edited By Uwe Engel, Anabel Quan-Haase, Sunny Liu, Lars E Lyberg Copyright 2022
    416 Pages 42 B/W Illustrations
    by Routledge

    416 Pages 42 B/W Illustrations
    by Routledge

    The Handbook of Computational Social Science is a comprehensive reference source for scholars across multiple disciplines. It outlines key debates in the field, showcasing novel statistical modeling and machine learning methods, and draws from specific case studies to demonstrate the opportunities and challenges in CSS approaches.

    The Handbook is divided into two volumes written by outstanding, internationally renowned scholars in the field. This first volume focuses on the scope of computational social science, ethics, and case studies. It covers a range of key issues, including open science, formal modeling, and the social and behavioral sciences. This volume explores major debates, introduces digital trace data, reviews the changing survey landscape, and presents novel examples of computational social science research on sensing social interaction, social robots, bots, sentiment, manipulation, and extremism in social media. The volume not only makes major contributions to the consolidation of this growing research field but also encourages growth in new directions.

    With its broad coverage of perspectives (theoretical, methodological, computational), international scope, and interdisciplinary approach, this important resource is integral reading for advanced undergraduates, postgraduates, and researchers engaging with computational methods across the social sciences, as well as those within the scientifi c and engineering sectors.


    1. Introduction to the Handbook of Computational Social Science
    2. Uwe Engel, Anabel Quan-Haase, Sunny Xun Liu and Lars Lyberg

      Section I. The Scope and Boundaries of CSS

    3. The Scope of Computational Social Science
    4. Claudio Cioffi-Revilla

    5. Analytical Sociology amidst a Computational Social Science Revolution
    6. Benjamin F. Jarvis, Marc Keuschnigg and Peter Hedström

    7. Computational Cognitive Modeling in the Social Sciences
    8. Holger Schultheis

    9. Computational Communication Science: Lessons from Working Group Sessions with Experts of an Emerging Research Field
    10. Stephanie Geise and Annie Waldherr

    11. A Changing Survey Landscape
    12. Lars Lyberg and Steven G. Heeringa

    13. Digital Trace Data: Modes of Data Collection, Applications, and Errors at a Glance
    14. Florian Keusch and Frauke Kreuter

    15. Open Computational Social Science
    16. Jan G. Voelkel and Jeremy Freese

    17. Causal and Predictive Modeling in Computational Social Science
    18. Uwe Engel

    19. Data-driven Agent-based Modeling in Computational Social Science
    20. Jan Lorenz

      Section II. Privacy, Ethics, and Politics in CSS Research

    21. Ethics and Privacy in Computational Social Science: A Call for Pedagogy
    22. William Hollingshead, Anabel Quan-Haase and Wenhong Chen

    23. Deliberating with the Public: An Agenda to Include Stakeholder Input on Municipal "Big Data" Projects
    24. James Popham, Jennifer Lavoie, Andrea Corradi and Nicole Coomber

    25. Analysis of the Principled-AI Framework´s Constraints in Becoming a Methodological Reference for Trustworthy-AI Design
    26. Daniel Varona and Juan Luis Suarez

      Section III. Case Studies and Research Examples

    27. Sensing Close-Range Proximity for Studying Face-to-Face Interaction
    28. Johann Schaible, Marcos Oliveira, Maria Zens and Mathieu Génois

    29. Social Media Data in Affective Science
    30. Max Pellert, Simon Schweighofer and David Garcia

    31. Understanding Political Sentiment: Using Twitter to Map the US 2016 Democratic Primaries
    32. Niklas M Loynes and Mark J Elliot

    33. The Social Influence of Bots and Trolls in Social Media
    34. Yimin Chen

    35. Social Bots and Social Media Manipulation in 2020: The Year in Review
    36. Ho-Chun Herbert Chang, Emily Chen, Meiqing Zhang, Goran Muric, and Emilio Ferrara

    37. A Picture is (still) Worth a Thousand Words: The Impact of Appearance and Characteristic Narratives on People’s Perceptions of Social Robots
    38. Sunny Xun Liu, Elizabeth Arredondo, Hannah Miezkowski, Jeff Hancock and Byron Reeves

    39. Data Quality and Privacy Concerns in Digital Trace Data: Insights from a Delphi Study on Machine Learning and Robots in Human Life
    40. Uwe Engel and Lena Dahlhaus

    41. Effective Fight Against Extremist Discourse On-Line: The Case of ISIS’s Propaganda
    42. Séraphin Alava and Rasha Nagem

    43. Public Opinion Formation on the Far Right

             Michael Adelmund and Uwe Engel


    Uwe Engel is Professor at the University of Bremen, Germany, where he held a chair in sociology from 2000 to 2020. From 2008 to 2013, Dr. Engel coordinated the Priority Programme on “Survey Methodology” of the German Research Foundation. His current research focuses on data science, human-robot interaction, and opinion dynamics.

    Anabel Quan-Haase is Professor of Sociology and Information and Media Studies at Western University and Director of the SocioDigital Media Lab, London, Canada. Her research interests include social media, social networks, life course, social capital, computational social science, and digital inequality/inclusion.

    Sunny Xun Liu is a research scientist at Stanford Social Media Lab, USA. Her research focuses on the social and psychological e- ects of social media and AI, social media and well-being, and how the design of social robots impacts psychological perceptions.

    Lars Lyberg was Head of the Research and Development Department at Statistics Sweden and professor at Stockholm University. He was an elected member of the International Statistical Institute. In 2018, he received the AAPOR Award for Exceptionally Distinguished Achievement.