Handbook of computational social science : theory, case studies and ethics
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 … celý popis
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- Další autoři:
- , , ,
- Typ dokumentu:
- Knihy
- Rozsah:
- xxi, 393 stran :
- Vydáno:
-
Abingdon, Oxon ; New York, NY :
Routledge,
2022.
- Vydání:
- 1st published 2022
- Edice:
- European association of methodology
- Témata:
- Fyzický popis:
- xxi, 393 stran : ilustrace, grafy ; 25 cm.
- Bibliografie:
- Obsahuje bibliografie a rejstřík
- ISBN:
- 978-0-367-45652-8
978-0-367-45653-5
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| 245 | 0 | 0 | |a Handbook of computational social science : |b theory, case studies and ethics / |c edited by Uwe Engel, Anabel Quan-Haase, Sunny Xun Liu and Lars Lyberg. |
| 246 | 2 | 3 | |a Handbook of computational social science : |b theory, case studies and ethics. Volume 1. |
| 250 | |a 1st published 2022 | ||
| 264 | 1 | |a Abingdon, Oxon ; |a New York, NY : |b Routledge, |c 2022. | |
| 300 | |a xxi, 393 stran : |b ilustrace, grafy ; |c 25 cm. | ||
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| 490 | 0 | |a European association of methodology | |
| 504 | |a Obsahuje bibliografie a rejstřík | ||
| 520 | |a 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. -- Provided by publisher. | ||
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