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Handbook of Computational Social Science, Volume 1 Uwe Engel

Handbook of Computational Social Science, Volume 1 By Uwe Engel

Handbook of Computational Social Science, Volume 1 by Uwe Engel

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Summary

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.

Handbook of Computational Social Science, Volume 1 Summary

Handbook of Computational Social Science, Volume 1: Theory, Case Studies and Ethics by Uwe Engel

1. Very comprehensive and extensive coverage (stresses the relevance of the entire research cycle, from design to data collection to analysis to interpretation).
2. Highlights the multidisciplinary nature of CSS, drawing from research in computer science, statistics, and the social and behavioural sciences.
3. Takes a holistic approach to CSS methods. Instead of focusing on simply harvesting data, the editors emphasise the importance of a carefully crafted research design containing key milestone checks.

About 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.

Table of Contents

Preface

  2. Introduction to the Handbook of Computational Social Science

  3. Uwe Engel, Anabel Quan-Haase, Sunny Xun Liu and Lars Lyberg

    Section I. The Scope and Boundaries of CSS

  4. The Scope of Computational Social Science

  5. Claudio Cioffi-Revilla

  6. Analytical Sociology amidst a Computational Social Science Revolution

  7. Benjamin F. Jarvis, Marc Keuschnigg and Peter Hedstroem

  8. Computational Cognitive Modeling in the Social Sciences

  9. Holger Schultheis

  10. Computational Communication Science: Lessons from Working Group Sessions with Experts of an Emerging Research Field

  11. Stephanie Geise and Annie Waldherr

  12. A Changing Survey Landscape

  13. Lars Lyberg and Steven G. Heeringa

  14. Digital Trace Data: Modes of Data Collection, Applications, and Errors at a Glance

  15. Florian Keusch and Frauke Kreuter

  16. Open Computational Social Science

  17. Jan G. Voelkel and Jeremy Freese

  18. Causal and Predictive Modeling in Computational Social Science

  19. Uwe Engel

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

  21. Jan Lorenz

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

  22. Ethics and Privacy in Computational Social Science: A Call for Pedagogy

  23. William Hollingshead, Anabel Quan-Haase and Wenhong Chen

  24. Deliberating with the Public: An Agenda to Include Stakeholder Input on Municipal Big Data Projects

  25. James Popham, Jennifer Lavoie, Andrea Corradi and Nicole Coomber

  26. Analysis of the Principled-AI Frameworks Constraints in Becoming a Methodological Reference for Trustworthy-AI Design

  27. Daniel Varona and Juan Luis Suarez

    Section III. Case Studies and Research Examples

  28. Sensing Close-Range Proximity for Studying Face-to-Face Interaction

  29. Johann Schaible, Marcos Oliveira, Maria Zens and Mathieu Genois

  30. Social Media Data in Affective Science

  31. Max Pellert, Simon Schweighofer and David Garcia

  32. Understanding Political Sentiment: Using Twitter to Map the US 2016 Democratic Primaries

  33. Niklas M Loynes and Mark J Elliot

  34. The Social Influence of Bots and Trolls in Social Media

  35. Yimin Chen

  36. Social Bots and Social Media Manipulation in 2020: The Year in Review

  37. Ho-Chun Herbert Chang, Emily Chen, Meiqing Zhang, Goran Muric, and Emilio Ferrara

  38. A Picture is (still) Worth a Thousand Words: The Impact of Appearance and Characteristic Narratives on People's Perceptions of Social Robots

  39. Sunny Xun Liu, Elizabeth Arredondo, Hannah Miezkowski, Jeff Hancock and Byron Reeves

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

  41. Uwe Engel and Lena Dahlhaus

  42. Effective Fight Against Extremist Discourse On-Line: The Case of ISIS's Propaganda

  43. Seraphin Alava and Rasha Nagem

  44. Public Opinion Formation on the Far Right

Michael Adelmund and Uwe Engel

Additional information

NLS9780367456528
9780367456528
0367456524
Handbook of Computational Social Science, Volume 1: Theory, Case Studies and Ethics by Uwe Engel
Uwe Engel
European Association of Methodology Series
New
Paperback
Taylor & Francis Ltd
2021-11-17
394
N/A
Book picture is for illustrative purposes only, actual binding, cover or edition may vary.
This is a new book - be the first to read this copy. With untouched pages and a perfect binding, your brand new copy is ready to be opened for the first time

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