Discovering and Categorising Language Biases in Reddit

Authors

  • Xavier Ferrer Department of Informatics, King’s College London, London
  • Tom van Nuenen Department of Informatics, King’s College London, London
  • Jose M. Such Department of Informatics, King’s College London, London
  • Natalia Criado Department of Informatics, King’s College London, London

Keywords:

Qualitative and quantitative studies of social media, Subjectivity in textual data; sentiment analysis; polarity/opinion identification and extraction, linguistic analyses of social media behavior, Text categorization; topic recognition; demographic/gender/age identification, Social network analysis; communities identification; expertise and authority discovery

Abstract

We present a data-driven approach using word embeddings to discover and categorise language biases on the discussion platform Reddit. As spaces for isolated user communities, platforms such as Reddit are increasingly connected to issues of racism, sexism and other forms of discrimination, signalling the need to monitor the language of these groups. One of the most promising AI approaches to trace linguistic biases in large textual datasets involves word embeddings, which transform text into high-dimensional dense vectors and capture semantic relations between words. Yet, previous studies require predefined sets of potential biases to study, e.g., whether gender is more or less associated with particular types of jobs. This makes these approaches unfit to deal with smaller and community-centric datasets such as those on Reddit, which contain smaller vocabularies and slang, as well as biases that may be particular to that community. This paper proposes a data-driven approach to automatically discover language biases encoded in the vocabulary of online discourse communities on Reddit. In our approach, protected attributes are connected to evaluative words found in the data, which are then categorised through a semantic analysis system. We verify the effectiveness of our method by comparing the biases we discover in the Google News dataset with those found in previous literature. We then successfully discover gender bias, religion bias, and ethnic bias in different Reddit communities. We conclude by discussing potential application scenarios and limitations of this data-driven bias discovery method.

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Published

2021-05-22

How to Cite

Ferrer, X., van Nuenen, T., Such, J. M., & Criado, N. (2021). Discovering and Categorising Language Biases in Reddit. Proceedings of the International AAAI Conference on Web and Social Media, 15(1), 140-151. Retrieved from https://ojs.aaai.org/index.php/ICWSM/article/view/18048