TY - JOUR
T1 - Offender–victim relationship and offender motivation in the context of indirect cyber abuse
T2 - A mixed-method exploratory analysis
AU - Vakhitova, Zarina
AU - Webster, Julianne
AU - Alston-Knox, Clair L.
AU - Reynald, Danielle
AU - Townsley, Michael
PY - 2018/9/1
Y1 - 2018/9/1
N2 - Cyber abuse can be executed directly (e.g. by sending derogatory emails or text messages addressed to the victim) or indirectly (e.g. by posting derogatory, private or false information, documents, images or videos about the victim online). This exploratory, mixed-method triangulated study examines cyber abuse crime events with the goal of identifying factors associated with the increased risk of personal victimization from both direct and indirect methods of cyber abuse. First, in-depth qualitative interviews with cyber abuse victims (n = 12) were conducted. The interviews were analysed using thematic analysis to generate hypotheses. These hypotheses were then tested using content analysis of newspaper reports (n = 110) and victims’ posts on online forums (n = 91) describing incidents of cyber abuse. Logistic regression using Bayesian Model Averaging analysis revealed that the combination of a prior offender–victim relationship and expressive motivation best predicts the use of indirect methods of cyber abuse, while direct methods of cyber abuse are more likely to occur when the offender does not know the victim and is motivated by instrumental ends. Implications for crime prevention are also discussed.
AB - Cyber abuse can be executed directly (e.g. by sending derogatory emails or text messages addressed to the victim) or indirectly (e.g. by posting derogatory, private or false information, documents, images or videos about the victim online). This exploratory, mixed-method triangulated study examines cyber abuse crime events with the goal of identifying factors associated with the increased risk of personal victimization from both direct and indirect methods of cyber abuse. First, in-depth qualitative interviews with cyber abuse victims (n = 12) were conducted. The interviews were analysed using thematic analysis to generate hypotheses. These hypotheses were then tested using content analysis of newspaper reports (n = 110) and victims’ posts on online forums (n = 91) describing incidents of cyber abuse. Logistic regression using Bayesian Model Averaging analysis revealed that the combination of a prior offender–victim relationship and expressive motivation best predicts the use of indirect methods of cyber abuse, while direct methods of cyber abuse are more likely to occur when the offender does not know the victim and is motivated by instrumental ends. Implications for crime prevention are also discussed.
KW - Bayesian Model Averaging
KW - Cyber abuse
KW - logistic regression
KW - offender motivation
KW - offender–victim relationship
UR - http://www.scopus.com/inward/record.url?scp=85050753786&partnerID=8YFLogxK
U2 - 10.1177/0269758017743073
DO - 10.1177/0269758017743073
M3 - Article
AN - SCOPUS:85050753786
SN - 0269-7580
VL - 24
SP - 347
EP - 366
JO - International Review of Victimology
JF - International Review of Victimology
IS - 3
ER -