Handbook of Computational Social Science, Volume 1
Theory, Case Studies and Ethics
1st Edition
Published on 17. November 2021
Book
Paperback/Softback
394 pages
978-0-367-45652-8 (ISBN)
Description
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.
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.
More details
Series
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
College/higher education
Professional and scholarly
Postgraduate and Professional
Illustrations
42 s/w Abbildungen, 2 s/w Photographien bzw. Rasterbilder, 40 s/w Zeichnungen, 22 s/w Tabellen
22 Tables, black and white; 40 Line drawings, black and white; 2 Halftones, black and white; 42 Illustrations, black and white
Dimensions
Height: 244 mm
Width: 170 mm
Thickness: 22 mm
Weight
718 gr
ISBN-13
978-0-367-45652-8 (9780367456528)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Uwe Engel | Anabel Quan-Haase | Sunny Liu
Handbook of Computational Social Science, Volume 1
Theory, Case Studies and Ethics
Book
11/2021
1st Edition
Routledge
€263.30
Shipment within 15-20 days
Uwe Engel | Anabel Quan-Haase | Sunny Liu
Handbook of Computational Social Science, Volume 1
Theory, Case Studies and Ethics
E-Book
11/2021
1st Edition
Routledge
€74.99
Available for download
Uwe Engel | Anabel Quan-Haase | Sunny Liu
Handbook of Computational Social Science, Volume 1
Theory, Case Studies and Ethics
E-Book
11/2021
1st Edition
Routledge
€74.99
Available for download
Persons
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.
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.
Content
Preface
Introduction to the Handbook of Computational Social Science
Uwe Engel, Anabel Quan-Haase, Sunny Xun Liu and Lars Lyberg
Section I. The Scope and Boundaries of CSS
The Scope of Computational Social Science
Claudio Cioffi-Revilla
Analytical Sociology amidst a Computational Social Science Revolution
Benjamin F. Jarvis, Marc Keuschnigg and Peter Hedstroem
Computational Cognitive Modeling in the Social Sciences
Holger Schultheis
Computational Communication Science: Lessons from Working Group Sessions with Experts of an Emerging Research Field
Stephanie Geise and Annie Waldherr
A Changing Survey Landscape
Lars Lyberg and Steven G. Heeringa
Digital Trace Data: Modes of Data Collection, Applications, and Errors at a Glance
Florian Keusch and Frauke Kreuter
Open Computational Social Science
Jan G. Voelkel and Jeremy Freese
Causal and Predictive Modeling in Computational Social Science
Uwe Engel
Data-driven Agent-based Modeling in Computational Social Science
Jan Lorenz
Section II. Privacy, Ethics, and Politics in CSS Research
Ethics and Privacy in Computational Social Science: A Call for Pedagogy
William Hollingshead, Anabel Quan-Haase and Wenhong Chen
Deliberating with the Public: An Agenda to Include Stakeholder Input on Municipal "Big Data" Projects
James Popham, Jennifer Lavoie, Andrea Corradi and Nicole Coomber
Analysis of the Principled-AI Framework?s Constraints in Becoming a Methodological Reference for Trustworthy-AI Design
Daniel Varona and Juan Luis Suarez
Section III. Case Studies and Research Examples
Sensing Close-Range Proximity for Studying Face-to-Face Interaction
Johann Schaible, Marcos Oliveira, Maria Zens and Mathieu Genois
Social Media Data in Affective Science
Max Pellert, Simon Schweighofer and David Garcia
Understanding Political Sentiment: Using Twitter to Map the US 2016 Democratic Primaries
Niklas M Loynes and Mark J Elliot
The Social Influence of Bots and Trolls in Social Media
Yimin Chen
Social Bots and Social Media Manipulation in 2020: The Year in Review
Ho-Chun Herbert Chang, Emily Chen, Meiqing Zhang, Goran Muric, and Emilio Ferrara
A Picture is (still) Worth a Thousand Words: The Impact of Appearance and Characteristic Narratives on People's Perceptions of Social Robots
Sunny Xun Liu, Elizabeth Arredondo, Hannah Miezkowski, Jeff Hancock and Byron Reeves
Data Quality and Privacy Concerns in Digital Trace Data: Insights from a Delphi Study on Machine Learning and Robots in Human Life
Uwe Engel and Lena Dahlhaus
Effective Fight Against Extremist Discourse On-Line: The Case of ISIS's Propaganda
Seraphin Alava and Rasha Nagem
Public Opinion Formation on the Far Right
Michael Adelmund and Uwe Engel
Introduction to the Handbook of Computational Social Science
Uwe Engel, Anabel Quan-Haase, Sunny Xun Liu and Lars Lyberg
Section I. The Scope and Boundaries of CSS
The Scope of Computational Social Science
Claudio Cioffi-Revilla
Analytical Sociology amidst a Computational Social Science Revolution
Benjamin F. Jarvis, Marc Keuschnigg and Peter Hedstroem
Computational Cognitive Modeling in the Social Sciences
Holger Schultheis
Computational Communication Science: Lessons from Working Group Sessions with Experts of an Emerging Research Field
Stephanie Geise and Annie Waldherr
A Changing Survey Landscape
Lars Lyberg and Steven G. Heeringa
Digital Trace Data: Modes of Data Collection, Applications, and Errors at a Glance
Florian Keusch and Frauke Kreuter
Open Computational Social Science
Jan G. Voelkel and Jeremy Freese
Causal and Predictive Modeling in Computational Social Science
Uwe Engel
Data-driven Agent-based Modeling in Computational Social Science
Jan Lorenz
Section II. Privacy, Ethics, and Politics in CSS Research
Ethics and Privacy in Computational Social Science: A Call for Pedagogy
William Hollingshead, Anabel Quan-Haase and Wenhong Chen
Deliberating with the Public: An Agenda to Include Stakeholder Input on Municipal "Big Data" Projects
James Popham, Jennifer Lavoie, Andrea Corradi and Nicole Coomber
Analysis of the Principled-AI Framework?s Constraints in Becoming a Methodological Reference for Trustworthy-AI Design
Daniel Varona and Juan Luis Suarez
Section III. Case Studies and Research Examples
Sensing Close-Range Proximity for Studying Face-to-Face Interaction
Johann Schaible, Marcos Oliveira, Maria Zens and Mathieu Genois
Social Media Data in Affective Science
Max Pellert, Simon Schweighofer and David Garcia
Understanding Political Sentiment: Using Twitter to Map the US 2016 Democratic Primaries
Niklas M Loynes and Mark J Elliot
The Social Influence of Bots and Trolls in Social Media
Yimin Chen
Social Bots and Social Media Manipulation in 2020: The Year in Review
Ho-Chun Herbert Chang, Emily Chen, Meiqing Zhang, Goran Muric, and Emilio Ferrara
A Picture is (still) Worth a Thousand Words: The Impact of Appearance and Characteristic Narratives on People's Perceptions of Social Robots
Sunny Xun Liu, Elizabeth Arredondo, Hannah Miezkowski, Jeff Hancock and Byron Reeves
Data Quality and Privacy Concerns in Digital Trace Data: Insights from a Delphi Study on Machine Learning and Robots in Human Life
Uwe Engel and Lena Dahlhaus
Effective Fight Against Extremist Discourse On-Line: The Case of ISIS's Propaganda
Seraphin Alava and Rasha Nagem
Public Opinion Formation on the Far Right
Michael Adelmund and Uwe Engel