Online crime, in general, is increasing these years, crimes committed through technology that is almost impossible for the authorities to solve and prevent. The average Danish teenager spends six hours a day on online forums, and studies on how content affects the user show that the users do get affected by the content. How do practitioners prevent teenage users from being embedded in extremist online communities when there are no national guidelines or research to support an evidence-based approach to prevention? Practitioners give presentations on this topic to teenagers and other professionals and seek to create stabile strong social bonds among peers and talk openly about pitfalls of the internet with the teenagers. This thesis applies Social Learning Theory and Social Bond theory in the understanding of why some users get radicalized through online forums. Applying these theories is relevant because mirroring propaganda, creating norm deviating social bonds and a “them and us” detachment from the surrounding norm society can be explained by these theoretical perspectives – and can all be precursors towards extremist behavior. The practitioners believe that they are navigating in a field where the need for knowledge is huge, and the methodological approach highly relies independently on the practitioner themselves. The main theoretical discussion is based on the founding hypothesis that being exposed to extremist content either leads to nothing or an increase in deviant behavior. The theoretical perspective in this thesis and previous research suggests that there is a causal link between traditional real-life risk factors and online crime, but also attachment to deviant online communities can lead to extremism – just as it is in a real-life setting.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:mau-43467 |
Date | January 2021 |
Creators | Thomsen, Nikolaj Møller |
Publisher | Malmö universitet, Malmö högskola, Institutionen för kriminologi (KR) |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
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