Abstract
Linguistic research into online grooming is scarce despite both the communicative essence of this form of online child sexual abuse and a substantial body of literature into it across other Social Sciences. Most of this literature has examined small data sets via qualitative methods, primarily thematic analysis; the exception being a couple of studies that have used automated software (Linguistic Inquiry and Word Count - LIWC) that operates at a single-word level. This study evaluates the contribution that a Corpus Assisted Discourse Studies (CADS) approach can make to this body of literature, with a focus on online groomers’ language. The corpus consists of >600 grooming chat logs taken from the Perverted Justice Foundation archive, from which the groomers’ language was extracted (c. 3.3 million words). Lexical dispersion (DPNorm), collocation and concordance analyses were conducted. The corpus was also run through LIWC. Our analysis shows that LIWC may not be the most efficient software to analyse online grooming language due to a lack of general language comparison scores, the non-transparency of some of its analytic variables and a focus on de-contextualised words. Comparatively, CADS methods can shed light upon online groomers’ strategic use of language. They can also reveal the complex and nuanced ways in which discourse features such as (im)explicitness and interpersonal (in)directness operate alongside these strategies.
Highlights
Sexual grooming of children online is a legally punishable form of Child Sexual Abuse (CSA), irrespective of whether it leads to off-line contact between the groomer and the child.1 Children who suffer online grooming/CSA are known to experience self-blame, depression and low-self-esteem; they may subsequently selfharm and develop behavioural problems (Hamilton-Giachritsis et al, 2017)
The main aim of this article is to explore the potential contribution of a Corpus As sisted Discourse Studies (CADS, ) approach to the study of a large corpus of online grooming interactions (‘chat logs’) extracted from the publicly available Perverted Justice archive, the language used by online groomers therein
In Linguistic Inquiry Word Count (LIWC) clout is an aggregated variable based on a closed source-code algorithm, which means that it is not possible to replicate its performance using different software tools – those provided within a Corpus Assisted Discourse Studies (CADS) approach in our case
Summary
Sexual grooming of children online is a legally punishable form of Child Sexual Abuse (CSA), irrespective of whether it leads to off-line (physical) contact between the groomer and the child. Children who suffer online grooming/CSA are known to experience self-blame, depression and low-self-esteem; they may subsequently selfharm and develop behavioural problems (Hamilton-Giachritsis et al, 2017). Children who suffer online grooming/CSA are known to experience self-blame, depression and low-self-esteem; they may subsequently selfharm and develop behavioural problems (Hamilton-Giachritsis et al, 2017). The impact of their communicative involvement online with a sexual predator can, in short, be as damaging as that ensuing from physical CSA (National Society for the Prevention of Cruelty to Children [NSPCC], 2017). The seriousness of the offence and its increasing prevalence over time (Bentley et al, 2018) may help account for a growing body of academic scholarship into online grooming over the past decade or so This scholarship has been primarily conducted within the disciplines of Criminology and Psychology. A subsidiary aim of our article, is to evaluate to what extent LIWC – as applied in those studies – and CADS methods may complement each other
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