Handbook of Computational Social Science, Volume 1: Theory, Case Studies and Ethics: European Association of Methodology Series
Editat de Uwe Engel, Anabel Quan-Haase, Sunny Liu, Lars E Lybergen Limba Engleză Paperback – 17 noi 2021
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.
| Toate formatele și edițiile | Preț | Express |
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| Paperback (1) | 440.77 lei 6-8 săpt. | |
| Taylor & Francis – 17 noi 2021 | 440.77 lei 6-8 săpt. | |
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| Taylor & Francis – 17 noi 2021 | 1285.80 lei 6-8 săpt. |
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Specificații
ISBN-10: 0367456524
Pagini: 416
Ilustrații: 84
Dimensiuni: 174 x 246 x 22 mm
Greutate: 0.83 kg
Ediția:1
Editura: Taylor & Francis
Colecția Routledge
Seria European Association of Methodology Series
Locul publicării:Oxford, United Kingdom
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Public țintă
Postgraduate and ProfessionalNotă biografică
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.
Cuprins
- Introduction to the Handbook of Computational Social ScienceUwe Engel, Anabel Quan-Haase, Sunny Xun Liu and Lars Lyberg
Section I. The Scope and Boundaries of CSS - The Scope of Computational Social ScienceClaudio Cioffi-Revilla
- Analytical Sociology amidst a Computational Social Science RevolutionBenjamin F. Jarvis, Marc Keuschnigg and Peter Hedström
- Computational Cognitive Modeling in the Social SciencesHolger Schultheis
- Computational Communication Science: Lessons from Working Group Sessions with Experts of an Emerging Research FieldStephanie Geise and Annie Waldherr
- A Changing Survey LandscapeLars Lyberg and Steven G. Heeringa
- Digital Trace Data: Modes of Data Collection, Applications, and Errors at a GlanceFlorian Keusch and Frauke Kreuter
- Open Computational Social ScienceJan G. Voelkel and Jeremy Freese
- Causal and Predictive Modeling in Computational Social ScienceUwe Engel
- Data-driven Agent-based Modeling in Computational Social ScienceJan Lorenz
Section II. Privacy, Ethics, and Politics in CSS Research - Ethics and Privacy in Computational Social Science: A Call for PedagogyWilliam Hollingshead, Anabel Quan-Haase and Wenhong Chen
- Deliberating with the Public: An Agenda to Include Stakeholder Input on Municipal "Big Data" ProjectsJames Popham, Jennifer Lavoie, Andrea Corradi and Nicole Coomber
- Analysis of the Principled-AI Framework´s Constraints in Becoming a Methodological Reference for Trustworthy-AI DesignDaniel Varona and Juan Luis Suarez
Section III. Case Studies and Research Examples - Sensing Close-Range Proximity for Studying Face-to-Face InteractionJohann Schaible, Marcos Oliveira, Maria Zens and Mathieu Génois
- Social Media Data in Affective ScienceMax Pellert, Simon Schweighofer and David Garcia
- Understanding Political Sentiment: Using Twitter to Map the US 2016 Democratic PrimariesNiklas M Loynes and Mark J Elliot
- The Social Influence of Bots and Trolls in Social MediaYimin Chen
- Social Bots and Social Media Manipulation in 2020: The Year in ReviewHo-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 RobotsSunny 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 LifeUwe Engel and Lena Dahlhaus
- Effective Fight Against Extremist Discourse On-Line: The Case of ISIS’s PropagandaSéraphin Alava and Rasha Nagem
- Public Opinion Formation on the Far Right
Descriere
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.