Predicting Recidivism among Internet Child Sex Sting Offenders Using Psychological Language Analysis

Drouin, Michelle and Boyd, Ryan L. and Greidanus Romaneli, Miriam (2018) Predicting Recidivism among Internet Child Sex Sting Offenders Using Psychological Language Analysis. Cyberpsychology, Behavior, and Social Networking, 21 (2). pp. 78-83. ISSN 2152-2715

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Abstract

In this study, we examined the extent to which computerized linguistic analysis of natural language data from chat transcripts of Internet child sex stings predicted recidivism among 334 convicted offenders. Using the Linguistic Inquiry and Word Count (LIWC) program, we found that reoffenders (including simultaneous and previous offenders) differed significantly from nonreoffenders in measures of clout (a composite measure of social dominance) and percentage of words used in the following linguistic categories: cognitive processes, personal pronoun use, insight, time, and ingestion. In contrast, total word count and percentage of sexual words, two categories that might be assumed to be predictive of recidivism, were not significantly different between these two groups. These analyses help to develop a typology for an Internet sex reoffender as one who is dominant, nonequivocating, and likely to discuss meeting with their target and/or parents' schedules. Moreover, they highlight the importance of examining the functional aspects of language in forensic linguistic analysis, and exemplify the utility of computerized linguistic analyses in the courtroom.

Item Type:
Journal Article
Journal or Publication Title:
Cyberpsychology, Behavior, and Social Networking
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2700
Subjects:
ID Code:
134826
Deposited By:
Deposited On:
22 Jun 2019 09:19
Refereed?:
Yes
Published?:
Published
Last Modified:
01 Dec 2020 07:08