Handbook of Computational Social Science Volume 1

<p>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.</p><p>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.</p><p>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.</p> <p>Preface</p><ol> <p> </p> <li>Introduction to the Handbook of Computational Social Science</li> <i> </i><p>Uwe Engel, Anabel Quan-Haase, Sunny Xun Liu and Lars Lyberg</p> <b> </b><p>Section I. The Scope and Boundaries of CSS</p> <p> </p> <li>The Scope of Computational Social Science</li> <i> </i><p>Claudio Cioffi-Revilla</p> <p> </p> <li>Analytical Sociology amidst a Computational Social Science Revolution</li> <i> </i><p>Benjamin F. Jarvis, Marc Keuschnigg and Peter Hedström</p> <p> </p> <li>Computational Cognitive Modeling in the Social Sciences</li> <i> </i><p>Holger Schultheis</p> <p> </p> <li>Computational Communication Science: Lessons from Working Group Sessions with Experts of an Emerging Research Field</li> <i> </i><p>Stephanie Geise and Annie Waldherr</p> <p> </p> <li>A Changing Survey Landscape</li> <i> </i><p>Lars Lyberg and Steven G. Heeringa</p> <p> </p> <li>Digital Trace Data: Modes of Data Collection, Applications, and Errors at a Glance</li> <i> </i><p>Florian Keusch and Frauke Kreuter</p> <p> </p> <li>Open Computational Social Science</li> <i> </i><p>Jan G. Voelkel and Jeremy Freese</p> <p> </p> <li>Causal and Predictive Modeling in Computational Social Science</li> <i> </i><p>Uwe Engel</p> <p> </p> <li>Data-driven Agent-based Modeling in Computational Social Science</li> <i> </i><p>Jan Lorenz</p> <b> </b><p>Section II. Privacy, Ethics, and Politics in CSS Research</p> <p> </p> <li>Ethics and Privacy in Computational Social Science: A Call for Pedagogy</li> <i> </i><p>William Hollingshead, Anabel Quan-Haase and Wenhong Chen</p> <p> </p> <li>Deliberating with the Public: An Agenda to Include Stakeholder Input on Municipal "Big Data" Projects</li> <i> </i><p>James Popham, Jennifer Lavoie, Andrea Corradi and Nicole Coomber</p> <p> </p> <li>Analysis of the Principled-AI Framework´s Constraints in Becoming a Methodological Reference for Trustworthy-AI Design</li> <i> </i><p>Daniel Varona and Juan Luis Suarez</p> <b> </b><p>Section III. Case Studies and Research Examples</p> <p> </p> <li>Sensing Close-Range Proximity for Studying Face-to-Face Interaction</li> <i> </i><p>Johann Schaible, Marcos Oliveira, Maria Zens and Mathieu Génois</p> <p> </p> <li>Social Media Data in Affective Science</li> <i> </i><p>Max Pellert, Simon Schweighofer and David Garcia</p> <p> </p> <li>Understanding Political Sentiment: Using Twitter to Map the US 2016 Democratic Primaries</li> <i> </i><p>Niklas M Loynes and Mark J Elliot</p> <p> </p> <li>The Social Influence of Bots and Trolls in Social Media</li> <i> </i><p>Yimin Chen</p> <p> </p> <li>Social Bots and Social Media Manipulation in 2020: The Year in Review</li> <i> </i><p>Ho-Chun Herbert Chang, Emily Chen, Meiqing Zhang, Goran Muric, and Emilio Ferrara</p> <p> </p> <li>A Picture is (still) Worth a Thousand Words: The Impact of Appearance and Characteristic Narratives on People’s Perceptions of Social Robots</li> <p><em>Sunny Xun Liu</em><em>, Elizabeth Arredondo, Hannah Miezkowski, Jeff Hancock and Byron Reeves</em></p> <p> </p> <li>Data Quality and Privacy Concerns in Digital Trace Data: Insights from a Delphi Study on Machine Learning and Robots in Human Life</li> <i> </i><p>Uwe Engel and Lena Dahlhaus</p> <p> </p> <li>Effective Fight Against Extremist Discourse On-Line: The Case of ISIS’s Propaganda</li> <i> </i><p>Séraphin Alava and Rasha Nagem</p> <p> </p> <li>Public Opinion Formation on the Far Right</li> </ol><p> <i>Michael Adelmund and Uwe Engel</i></p>