| spelling |
oapen-20.500.12657-514102021-11-11T11:19:24Z 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 bic Book Industry Communication::J Society & social sciences::JM Psychology bic Book Industry Communication::J Society & 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." 2021-11-11T10:41:33Z 2021-11-11T10:41:33Z 2021 book 9780367456535 9780367456528 9781003024583 https://library.oapen.org/handle/20.500.12657/51410 eng Taylor & Francis Routledge 7b3c7b10-5b1e-40b3-860e-c6dd5197f0bb 3ec5b7b8-ae9c-4b40-81a7-40f8399dc628 c9588332-6701-4dd1-9f83-6a24d5c355de 713ace0f-8881-4392-be32-a2f3adc885d6 043cd7c3-4a5c-409e-a0c3-a93718ae7ffc 69f53bf5-b1d1-4b62-b16e-5603d0179822 9780367456535 9780367456528 9781003024583 Routledge open access
|
| 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."
|
