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Online grooming has become a wide-spread and worryingly fast increasing issue in society. This thesis analyses a corpus of online grooming communication, made available by the Perverted Justice (PJ) archive, a non-profit organisation that from 2004 until 2019 employed volunteers, who pretended to be children and entered chat rooms to catch and convict groomers, collaborating with law enforcement. The archive consists of 622 grooming chat logs and approx. 3.7 million words of groomer language. A corpus of this database was built, and a Corpus-Assisted Discourse Studies (CADS) approach used to analyse the language therein. Specifically, the language was compared to a reference corpus of general chat language data (PAN2012) and duration of online grooming and manipulative requesting behaviour were also investigated. The following research questions were answered: 1)What are the features of a corpus of online groomer language compared to that of a general digital chat language reference corpus? Is online groomer language distinct? How are online grooming intentions realised linguistically by online groomers?2)Does duration of grooming influence the grooming process/intentions? Is usage of specific words/specific grooming intentions associated with different duration of grooming? Can different duration profiles be established and, if so, what are the cut-off points for these duration profiles?3)How are requests realised in online grooming and how does duration influence this? How do groomers make requests and what support move functions do they use? Does duration influence how requests are made, and the type of support move function that are used?The thesis newly identifies nuanced linguistic realisations of groomers’ intentions and strategies, proposing a new working terminology for discourse-based models of online grooming. This is based on a review of the literature followed by an empirical analysis refining this terminology, which has not been done before. It finds evidence for two distinct duration-based grooming approaches and yields a fine-grained qualitative analysis of groomer requests, also influenced by grooming duration. There have only been very few studies using a CADS analysis of such a large dataset of groomer language and this thesis will lead to new insights, implications and significance for the successful analysis, detection and prevention of online grooming.
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Stored only when both papers are in the corpus — 16 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.