Titlebook: Understanding Recruitment to Organized Crime and Terrorism; David Weisburd,Ernesto U. Savona,Francesco Caldero Book 2020 Springer Nature S

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Investigating the Psychological Profile of Organized Crime Membersevertheless, the majority of studies focused on specific classes of perpetrator belonging to non-organized crime (NOC) groups. Concerning organised crime (OC), the psychological evidence is scanty with only a few studies focusing on personality traits. Here we tested 100 prisoners (50 OC and 50 NOC

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Traffickers in Transit: Analysing the Logistics and Involvement Mechanisms of Organised Crime at Loggistical nodes in the world economy, like the airport and the seaport. Although knowledge on organised crime offenders engaging in transit crime has accumulated recently, systematic analyses of offenders operating on logistical nodes are still rare..Based on in-depth analyses of 16 cases of the Dutc

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Delinquent Development, Employment and Income in a Sample of Dutch Organized Crime Offenders: Shape,rs to social economic factors such as employment and income. Other chapters in this volume provide systematic reviews of the literature regarding criminal careers of specific – largely understudied – groups, such as criminal careers of organized crime offenders (e.g. Savona et al. 2020). Reviews of

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Book 2020fically explores the social, situational, psychological, and economic drivers of recruitment. Although organized crime networks and terrorism networks can differ in underlying goals and motivations, this volume demonstrates common drivers in their recruitment, which will provide insights for crime p

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Introduction,ize how they have added to the knowledge base in this area. Finally, we revisit the question of similarities and differences between factors influencing recruitment based on the papers in the volume, and try to draw broader conclusions about how this knowledge can inform societal responses to the problem of recruitment.

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Tomer Carmel,Michael Wolfowicz,Badi Hasisi,David Weisburdfake, defamatory, and hateful posts are further evaluated to determine their status. In this research work, several SOTA BERT-based techniques are also subjected to comparative analysis. Our proposed model is found to perform better than the baseline model for all the hostile subclasses (defamation, fake, hate, and offensive).