Final published version
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - Predicting Recidivism among Internet Child Sex Sting Offenders Using Psychological Language Analysis
AU - Drouin, Michelle
AU - Boyd, Ryan L.
AU - Greidanus Romaneli, Miriam
PY - 2018/2/1
Y1 - 2018/2/1
N2 - 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.
AB - 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.
KW - forensic linguistic analysis
KW - internet sex offenders
KW - language analysis
KW - recidivism
KW - sex sting offenders
U2 - 10.1089/cyber.2016.0617
DO - 10.1089/cyber.2016.0617
M3 - Journal article
C2 - 28609206
AN - SCOPUS:85041738938
VL - 21
SP - 78
EP - 83
JO - Cyberpsychology, Behavior, and Social Networking
JF - Cyberpsychology, Behavior, and Social Networking
SN - 2152-2715
IS - 2
ER -