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Handbook of Computational Social Science, Volume 1: Theory, Case Studies and Ethics [Hardback]

Edited by , Edited by , Edited by , Edited by (University of Bremen, Germany)
  • Formāts: Hardback, 394 pages, height x width: 246x174 mm, weight: 453 g, 22 Tables, black and white; 40 Line drawings, black and white; 2 Halftones, black and white; 42 Illustrations, black and white
  • Sērija : European Association of Methodology Series
  • Izdošanas datums: 17-Nov-2021
  • Izdevniecība: Routledge
  • ISBN-10: 0367456532
  • ISBN-13: 9780367456535
  • Hardback
  • Cena: 236,78 €
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  • Formāts: Hardback, 394 pages, height x width: 246x174 mm, weight: 453 g, 22 Tables, black and white; 40 Line drawings, black and white; 2 Halftones, black and white; 42 Illustrations, black and white
  • Sērija : European Association of Methodology Series
  • Izdošanas datums: 17-Nov-2021
  • Izdevniecība: Routledge
  • ISBN-10: 0367456532
  • ISBN-13: 9780367456535
"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 socialscience, 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 into 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 scientific and engineering sectors"--

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 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 into 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 scientific and engineering sectors.

List of contributors x
Preface xx
1 Introduction to the Handbook of Computational Social Science
1(14)
Uwe Engel
Anabel Quan-Haase
Sunny Xun Liu
Lars Lyberg
Section I The scope and boundaries of CSS 15(154)
2 The scope of computational social science
17(16)
Claudio Cioffi-Revilla
3 Analytical sociology amidst a computational social science revolution
33(20)
Benjamin F. Jarvis
Marc Keuschnigg
Peter Hedstrom
4 Computational cognitive modeling in the social sciences
53(13)
Holger Schultheis
5 Computational communication science: lessons from working group sessions with experts of an emerging research field
66(17)
Stephanie Geise
Annie Waldherr
6 A changing survey landscape
83(17)
Lars Lyberg
Steven G. Heeringa
7 Digital trace data: modes of data collection, applications, and errors at a glance
100(19)
Florian Keusch
Frauke Kreuter
8 Open computational social science
119(12)
Jan G. Voelkel
Jeremy Freese
9 Causal and predictive modeling in computational social science
131(19)
Uwe Engel
10 Data-driven agent-based modeling in computational social science
150(19)
Jan Lorenz
Section II Privacy, ethics, and politics in CSS research 169(48)
11 Ethics and privacy in computational social science: a call for pedagogy
171(15)
William Hollingshead
Anabel Quan-Haase
Wenhong Chen
12 Deliberating with the public: an agenda to include stakeholder input on municipal "big data" projects
186(14)
James F. Popham
Jennifer Lavoie
Andrea Corradi
Nicole Coomber
13 Analysis of the principled AI framework's constraints in becoming a methodological reference for trustworthy AI design
200(17)
Daniel Varona
Juan Luis Suarez
Section III Case studies and research examples 217(163)
14 Sensing close-range proximity for studying face-to-face interaction
219(21)
Johann Schaible
Marcos Oliveira
Maria Zens
Mathieu Genois
15 Social media data in affective science
240(16)
Max Pellert
Simon Schweighofer
David Garcia
16 Understanding political sentiment: using Twitter to map the U.S. 2016 Democratic primaries
256(31)
Niklas M. Loynes
Mark Elliot
17 The social influence of bots and trolls in social media
287(17)
Yim in Chen
18 Social bots and social media manipulation in 2020: the year in review
304(20)
Ho-Chun Herbert Chang
Emily Chen
Meiqing Zhang
Goran Muric
Emilio Ferrara
19 A picture is (still) worth a thousand words: the impact of appearance and characteristic narratives on people's perceptions of social robots
324(19)
Sunny Xun Liu
Elizabeth Arredondo
Hannah Mieczkowski
Jeff Hancock
Byron Reeves
20 Data quality and privacy concerns in digital trace data: insights from a Delphi study on machine learning and robots in human life
343(20)
Uwe Engel
Lena Dahlhaus
21 Effective fight against extremist discourse online: the case of ISIS's propaganda
363(10)
Seraphin Alava
Rasha Nagem
22 Public opinion formation on the far right
373(7)
Michael Adelmund
Uwe Engel
Index 380
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.