Handbook of Computational Social Science, Vol 1

"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...

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Định dạng: Online
Ngôn ngữ:Tiếng Anh
Được phát hành: Taylor & Francis 2021
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Truy cập trực tuyến:OCN: 1282299052
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collection Directory of Open Access Books
description "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."
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publishDateRange 2021
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publisher Taylor & Francis
publisherStr Taylor & Francis
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spelling doab-20.500.12854ir-727652025-08-13T14:11:41Z Handbook of Computational Social Science, Vol 1 Engel, Uwe Quan-Haase, Anabel Xun Liu, Sunny Lyberg, Lars 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 thema EDItEUR::J Society and Social Sciences::JM Psychology thema EDItEUR::J Society and Social Sciences::JM Psychology::JMB Psychological methodology thema EDItEUR::J Society and Social Sciences::JM Psychology thema EDItEUR::J Society and Social Sciences::JM Psychology::JMB Psychological methodology "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." 2021-11-12T04:07:21Z 2021-11-12T04:07:21Z 2021-11-11T10:41:33Z 2021 book OCN: 1282299052 https://library.oapen.org/handle/20.500.12657/51410 9780367456535 9780367456528 9781003024583 https://directory.doabooks.org/handle/20.500.12854/72765 eng open access Taylor & Francis Routledge fa69b019-f4ee-4979-8d42-c6b6c476b5f0 Chapter 3 Analytical Sociology amidst a Computational Social Science Revolution Chapter 7 Digital Trace Data Chapter 9 Causal and Predictive Modeling in Computational Social Science Chapter 20 Data Quality and Privacy concerns in Digital Trace Data Chapter 21 Effective Fight against Extremist Discourse Online 9780367456535 9780367456528 9781003024583 Routledge open access
spellingShingle 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
thema EDItEUR::J Society and Social Sciences::JM Psychology
thema EDItEUR::J Society and Social Sciences::JM Psychology::JMB Psychological methodology
thema EDItEUR::J Society and Social Sciences::JM Psychology
thema EDItEUR::J Society and Social Sciences::JM Psychology::JMB Psychological methodology
Handbook of Computational Social Science, Vol 1
title Handbook of Computational Social Science, Vol 1
title_full Handbook of Computational Social Science, Vol 1
title_fullStr Handbook of Computational Social Science, Vol 1
title_full_unstemmed Handbook of Computational Social Science, Vol 1
title_short Handbook of Computational Social Science, Vol 1
title_sort handbook of computational social science vol 1
topic 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
thema EDItEUR::J Society and Social Sciences::JM Psychology
thema EDItEUR::J Society and Social Sciences::JM Psychology::JMB Psychological methodology
thema EDItEUR::J Society and Social Sciences::JM Psychology
thema EDItEUR::J Society and Social Sciences::JM Psychology::JMB Psychological methodology
topic_facet 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
thema EDItEUR::J Society and Social Sciences::JM Psychology
thema EDItEUR::J Society and Social Sciences::JM Psychology::JMB Psychological methodology
thema EDItEUR::J Society and Social Sciences::JM Psychology
thema EDItEUR::J Society and Social Sciences::JM Psychology::JMB Psychological methodology
url OCN: 1282299052