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The Past, Present, and Future of Computational Social Science

EPJ Data Science is bringing together a Topical Collection on The Past, Present, and Future of Computational Social Science

Computational Social Science is a rapidly evolving scientific discipline. Theoretical, methodological, and empirical innovations are simultaneously produced in a variety of traditional scientific fields, such as the social sciences, computer science, mathematics and statistics, physics, psychology, and communication research.
This Topical Collection aims at exploring disciplinary gaps and learning opportunities. It builds upon cross-disciplinary reviews and discussions of keynote presentations at the community's prime conference: The International Conference on Computational Social Science (IC2S2) in 2021. Through these pieces, it aims at contributing to an understanding of the past, present and future opportunities for the field of computational social science.

Guest Editors:
Termeh Shafie, GESIS Cologne, Germany
Christoph Stadtfeld, ETH Zurich, Switzerland

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  1. In this paper, we engage with and expand on the keynote talk about the “Right to Audit” given by Prof. Christian Sandvig at the International Conference on Computational Social Science 2021 through a critical ...

    Authors: Aleksandra Urman, Ivan Smirnov and Jana Lasser
    Citation: EPJ Data Science 2024 13:19
  2. Deductive and theory-driven research starts by asking questions. Finding tentative answers to these questions in the literature is next. It is followed by gathering, preparing and modelling relevant data to em...

    Authors: Aliakbar Akbaritabar
    Citation: EPJ Data Science 2024 13:14
  3. In her 2021 IC2S2 keynote talk, “Critical Data Theory,” Margaret Hu builds off Critical Race Theory, privacy law, and big data surveillance to grapple with questions at the intersection of big data and legal j...

    Authors: Sarah Shugars
    Citation: EPJ Data Science 2024 13:13
  4. There is an ongoing shift in computational social science towards validating our methodologies and improving the reliability of our findings. This is tremendously exciting in that we are moving beyond explorat...

    Authors: Carolina E. S. Mattsson
    Citation: EPJ Data Science 2024 13:3
  5. Puberty is a phase in which individuals often test the boundaries of themselves and surrounding others and further define their identity – and thus their uniqueness compared to other individuals. Similarly, as...

    Authors: Timon Elmer
    Citation: EPJ Data Science 2023 12:58

Annual journal metrics

  • 2022 Citation Impact
    3.6 - 2-year Impact Factor
    4.4 - 5-year Impact Factor
    1.625 - SNIP (Source Normalized Impact per Paper)
    1.066 - SJR (SCImago Journal Rank)

    2023 Speed
    20 days submission to first editorial decision for all manuscripts (Median)
    234 days submission to accept (Median)

    2023 Usage 
    578,929 downloads
    824 Altmetric mentions 

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