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            Chapter 2 A brief history of Apis

            Limitations and opportunities for online research

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            Author(s)
            Jünger, Jakob
            Language
            English
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            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."
            Book
            Handbook of Computational Social Science, Volume 2; Handbook of Computational Social Science, Volume 2
            URI
            https://doab-dev.siscern.org/handle/20.500.12854/157347
            Keywords
            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
            DOI
            10.4324/9781003025245-3
            ISBN
            9780367456535, 9780367456528
            Publisher
            Taylor & Francis
            Publisher website
            http://www.taylorandfrancis.com/
            Publication date and place
            2021
            Imprint
            Routledge
            Pages
            17
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            Credits


            • logo Investir l'avenirInvestir l'avenir
            • logo MESRIMESRI
            • logo EUEuropean Union
              This project received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 871069.

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