Linguistic analysis of suspected child sexual offenders’ interactions in a dark web image exchange chatroom


  • Emily Chiang Aston Institute for Forensic Linguistics
  • Dong Nguyen Utrecht University
  • Amanda Towler Hyperion Gray
  • Mark Haas Hyperion Gray
  • Jack Grieve University of Birmingham



dark web, child sexual abuse, indecent images of children, move analysis, rhetorical structure, undercover police


Child sexual offenders convene in dark web spaces to exchange indecent imagery, advice and support. In response, law enforcement agencies deploy undercover agents to pose as offenders online to gather intelligence on these offending communities. Currently, however, little is known about how offenders interact online, which raises significant questions around how undercover officers should ‘authentically’ portray the persona of a child sexual offender. This article presents the first linguistic description of authentic offender–offender interactions taking place on a dark web image exchange chatroom. Using move analysis, we analyse chatroom users’ rhetorical strategies. We then model the move sequences of different users and user types using Markov chains, to make comparisons between their linguistic behaviours. We find the predominant moves characterising this chatroom are Offering Indecent Images, Greetings, Image Appreciation, General Rapport and Image Discussion, and that rhetorical strategies differ between users of different levels of offending and dark web image-sharing experience.

Author Biographies

  • Emily Chiang, Aston Institute for Forensic Linguistics

    Emily Chiang is a postdoctoral research associate at the Aston Institute for Forensic Linguistics. She explores linguistic expressions of identity in online sexual abuse interactions. Current research interests include self-styled ‘paedophile- hunting’ groups and linguistic variation over the lifespan.

  • Dong Nguyen, Utrecht University

    Dong Nguyen was previously a Fellow at the Alan Turing Institute, and is now an assistant professor at Utrecht University. She has worked on various topics in Natural Language Processing and Information Retrieval, and is especially interested in computational text analysis for research questions from the social sciences.

  • Amanda Towler, Hyperion Gray

    Amanda Towler is a computer security analyst at Hyperion Gray.

  • Mark Haas, Hyperion Gray

    Mark Haas is a senior engineer at Hyperion Gray.

  • Jack Grieve, University of Birmingham

    Jack Grieve is a professor of corpus linguistics at the University of Birmingham. His research interests include corpus linguistics, sociolinguistics, and forensic linguistics.


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How to Cite

Chiang, E., Nguyen, D., Towler, A., Haas, M., & Grieve, J. (2021). Linguistic analysis of suspected child sexual offenders’ interactions in a dark web image exchange chatroom. International Journal of Speech, Language and the Law, 27(2), 129-161.