Cyberbullying perpetration

An empirical test of social learning theory in Iran

Datos Bibliográficos

ID2153242
AutoresSeyyed Masoomeh Shadmanfaat (University of Guilan), C Jordan Howell (0000-0003-4443-5068, University of South Florida, Tampa, USA), Caitlyn N Muniz (0000-0001-8572-5075, University of Texas at El Paso, El Paso, USA), John K Cochran (0000-0001-5227-1564, University of South Florida, Tampa, USA, autor de correspondencia), Saeed Kabiri (0000-0001-5022-887X, University of Mazandaran, Babolsar, Iran), Eva M Fontaine (University of South Florida, Tampa, USA)
Año2020
Volumen41
Número3
Páginas278-293
Fecha de publicación2020-03-03
Peer ReviewedSí
Open AccessNo
TipoARTICLE
RevistaDeviant Behavior (JOURNAL)
Identificadores de la revistaISSN: 0163-9625 • E-ISSN: 1521-0456
EditorialInforma UK Limited (PUBLISHER • GB)
DOI10.1080/01639625.2019.1565513
OpenAlexW2910939602
IdiomaEN
Citas recibidas32
Referencias citadas65

To test social learning theory's ability to explain Iranian sports fans' decision to engage in cyberbullying perpetration against rivals, a random sample of 464 students from an Iranian university is employed. Structural equation modeling is used to analyze these data. Findings suggest that cyberbullying against rivals is significantly predicted by differential association, definitions, imitation, and differential reinforcement. In addition, differential association also has direct effects on definitions, imitation, and differential reinforcement, and from these paths, indirect effects (partial mediation) on cyberbullying perpetration

Association (psychology · Differential (mechanical device · Differential association · Imitation · Mediation · Political science · Reinforcement · Sample (material · Social learning theory · Statistics · Structural equation modeling · Test (biology · Bullying, Victimization, and Aggression · Engineering · Hate Speech and Cyberbullying Detection · Mathematics · Psychology · Social Psychology · Stalking, Cyberstalking, and Harassment