Big Five personality traits of cybercrime victims
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Leukfeldt, E Rutger
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Abstract
The prevalence of cybercrime has increased rapidly over the last decades and has become part of the everyday life of citizens. It is, therefore, of great importance to gain more knowledge on the factors related to an increased or decreased likelihood of becoming a cybercrime victim. The current study adds to the existing body of knowledge using a large representative sample of Dutch individuals (N = 3,648) to study the relationship between cybercrime victimization and the key traits from the Big Five model of personality (i.e., extraversion, agreeableness, conscientiousness, emotional stability, and openness to experience). First, multinomial logistic regression analyses were used to examine the associations between the personality traits and three victim groups, that is, cybercrime victims versus nonvictims, traditional crime victims versus nonvictims, and cybercrime victims versus traditional crime victims. Next, logistic regression analyses were performed to predict victimization of cyber-dependent crimes (i.e., hacking and virus infection) and cyber-enabled crimes (i.e., online intimidation, online consumer fraud, and theft from bank account). The analyses show that personality traits are not specifically associated with cybercrime victimization, but rather with victimization in general. Only those with higher scores on emotional stability were less likely to become a victim of cybercrime than traditional crime. Furthermore, the results indicate that there are little differences between personality traits related to victimization of cyber-enabled and cyber-dependent crimes. Only individuals with higher scores on openness to experience have higher odds of becoming a victim of cyber-enabled crimes.
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Cyberpsychology, Behavior, and Social Networking
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20
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7
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Psychology
Cognitive and computational psychology
Big Five
cybercrime
hacking
online fraud
personality
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van de Weijer, SGA; Leukfeldt, ER, Big Five personality traits of cybercrime victims, Cyberpsychology, Behavior, and Social Networking, 2017, 20 (7), pp. 407-412