Handbook of Computational Social Science, Volume 2

"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 opportuni...

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Bibliographic Details
Other Authors: Engel, Uwe (Editor), Quan-Haase, Anabel (Editor), Xun Liu, Sunny (Editor), Lyberg, Lars (Editor)
Format: eBook
Published: Taylor & Francis 2021
Subjects:
Online Access:Get fulltext
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100 1 |a Engel, Uwe  |e edt 
856 |z Get fulltext  |u https://library.oapen.org/handle/20.500.12657/51439 
700 1 |a Quan-Haase, Anabel  |e edt 
700 1 |a Xun Liu, Sunny  |e edt 
700 1 |a Lyberg, Lars  |e edt 
700 1 |a Engel, Uwe  |e oth 
700 1 |a Quan-Haase, Anabel  |e oth 
700 1 |a Xun Liu, Sunny  |e oth 
700 1 |a Lyberg, Lars  |e oth 
245 1 0 |a Handbook of Computational Social Science, Volume 2 
260 |b Taylor & Francis  |c 2021 
506 0 |a Open Access  |2 star  |f Unrestricted online access 
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." 
540 |a All rights reserved 
546 |a English 
650 7 |a Psychology  |2 bicssc 
650 7 |a Psychological methodology  |2 bicssc 
653 |a AI, big data, data analysis, data archives, data ownership, data science, digital trace, ethical standards, ethics, human-robot interaction, information technology, machine learning, open data, politics, policy, quantitative, replication, social, social media, socio-robots, survey data, survey design, survey methodology, unstructured data