A

Benchmarking Crisis in Social Media Analytics: A Solution for the Data-Sharing Problem

Social Science Computer Review, vol. 40, pp. 1496–1522

Abstract

Computational social science uses computational and statistical methods in order to evaluate social interaction. The public availability of data sets is thus a necessary precondition for reliable and replicable research. These data allow researchers to benchmark the computational methods they develop, test the generalizability of their findings, and build confidence in their results. When social media data are concerned, data sharing is often restricted for legal or privacy reasons, which makes the comparison of methods and the replicability of research results infeasible. Social media analytics research, consequently, faces an integrity crisis. How is it possible to create trust in computational or statistical analyses, when they cannot be validated by third parties? In this work, we explore this well-known, yet little discussed, problem for social media analytics. We investigate how this problem can be solved by looking at related computational research areas. Moreover, we propose and implement a prototype to address the problem in the form of a new evaluation framework that enables the comparison of algorithms without the need to exchange data directly, while maintaining flexibility for the algorithm design.

Authors 9

  1. Dennis Assenmacher corresponding

    Queensland University of Technology · University of Münster

    Affiliation as printed

    Queensland University of Technology (QUT), Brisbane, Australia

    University of Münster, Germany

  2. Defence Science and Technology Group · Department of Defence · The University of Adelaide

    Affiliation as printed

    Defence Science and Technology Group, Department of Defence, Canberra, Australian Capital Territory, Australia

    University of Adelaide, South Australia, Australia

  3. Mike Preuß Aachen

    Leiden University

    Affiliation as printed

    Universiteit Leiden, the Netherlands

  4. RWTH Aachen University

    Affiliation as printed

    RWTH Aachen University, Germany

  5. University of Edinburgh

    Affiliation as printed

    University of Edinburgh, United Kingdom

  6. Institute of Informatics and Telematics

    Affiliation as printed

    Institute of Informatics and Telematics (IIT-CNR), Pisa, Italy

  7. University of Münster

    Affiliation as printed

    University of Münster, Germany

  8. The University of Adelaide

    Affiliation as printed

    University of Adelaide, South Australia, Australia

  9. University of Münster

    Affiliation as printed

    University of Münster, Germany

Cited by 26 stored of 26

No patents citing this paper on Lens.org (checked 2026-10-06).

References 72