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dc.contributor.editorEngel, Uwe
dc.contributor.editorQuan-Haase, Anabel
dc.contributor.editorXun Liu, Sunny
dc.contributor.editorLyberg, Lars
dc.date.accessioned2021-11-11T10:41:33Z
dc.date.available2021-11-11T10:41:33Z
dc.date.issued2021
dc.identifier.urihttps://library.oapen.org/handle/20.500.12657/51410
dc.description.abstract"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."en_US
dc.languageEnglishen_US
dc.subject.classificationbic Book Industry Communication::J Society & social sciences::JM Psychologyen_US
dc.subject.classificationbic Book Industry Communication::J Society & social sciences::JM Psychology::JMB Psychological methodologyen_US
dc.subject.otherAI, 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 dataen_US
dc.titleHandbook of Computational Social Science, Vol 1en_US
dc.title.alternativeTheory, Case Studies and Ethicsen_US
dc.typebook
oapen.relation.isPublishedBy7b3c7b10-5b1e-40b3-860e-c6dd5197f0bben_US
oapen.relation.hasChapter3ec5b7b8-ae9c-4b40-81a7-40f8399dc628
oapen.relation.hasChapterc9588332-6701-4dd1-9f83-6a24d5c355de
oapen.relation.hasChapter713ace0f-8881-4392-be32-a2f3adc885d6
oapen.relation.hasChapter043cd7c3-4a5c-409e-a0c3-a93718ae7ffc
oapen.relation.hasChapter69f53bf5-b1d1-4b62-b16e-5603d0179822
oapen.relation.isbn9780367456535en_US
oapen.relation.isbn9780367456528en_US
oapen.relation.isbn9781003024583en_US
oapen.imprintRoutledgeen_US


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