Ch. 5: Applying Machine Learning to Online Data? Beware! Computational Social Science Requires Care.

Creative Commons License

Bayram U.

in: Opportunities and Challenges for Computational Social Science Methods, Enes Abanoz, Editor, IGI Global, Pennsylvania, pp.100-125, 2022

  • Publication Type: Book Chapter / Chapter Research Book
  • Publication Date: 2022
  • Publisher: IGI Global
  • City: Pennsylvania
  • Page Numbers: pp.100-125
  • Editors: Enes Abanoz, Editor
  • Çanakkale Onsekiz Mart University Affiliated: Yes


The immense impact of social media on contemporary cultural evolution is undeniable, consequently declaring them an essential data source for computational social science studies. Alongside the advancements in natural language processing and machine learning disciplines, computational social science researchers continuously adapt new techniques to the data collected from social media. Although these developments are imperative for studying the sociological transformations in many communities, there are some inconspicuous problems on the horizon. This chapter addresses issues that may arise from the use of social media data, like biased models. It also discusses various obstacles associated with machine learning methods while also providing possible solutions and recommendations to overcome these struggles from an interdisciplinary perspective. In the long term, this chapter will guide computational social science researchers in their future studies, from things to be aware of with data collection to assembling an accurate experimental design.