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

Emily Chiang, Dong Nguyen, Amanda Towler, Mark Haas, Jack Grieve

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish
Pages (from-to)129-161
Number of pages33
JournalInternational Journal of Speech, Language and the Law
Issue number2
Publication statusPublished - 21 May 2021

Bibliographical note

Available only under the terms of the Creative Commons CC BY-NC-ND licence.

Funding: This work was supported by the Alan Turing Institute under the Defence & Security programme.


  • Child sexual abuse
  • Dark web
  • Indecent images of children
  • Move analysis
  • Rhetorical structure
  • Undercover police


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