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Journal of Hate Studies

Abstract

Online extremism, or the use of information technology to profess attitudes devaluing others based on a characteristic such as race, religion, gender, or sexuality, is a growing problem. This has led to myriad harmful effects for some who are exposed to online hate. A critical first step toward stemming the tide of online hate is understanding factors associated with its creation and spread. To that end, this analysis examines factors associated with joining an ongoing attack against a targeted group online. We use insights from four leading criminological theories – routine activity theory, social control theory, general strain theory, and social learning/differential association theory - to investigate who is likely to join an attack on a targeted group when they view such an attack occurring. Using data from a national sample of 15 – 36-year-old Internet users, we conduct an ordinal logistic regression analysis. Results show support for social control theory and strain theory, as low levels of self-control and online strain are both positively correlated with joining an online attack. Similarly, we find support for the applicability of social learning theory; close engagement with online friends and groups is related to an increased likelihood of joining in online hate. Routine activity theory, however, is less relevant for understanding our outcome. Taken together, our findings shed light on factors associated with the perpetuation of online hate, and, in doing so, offer avenues for reducing its growth.

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

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