DETECTING AND ANALYZING CYBERCRIME IN TEXT-BASED COMMUNICATION OF CYBERCRIMINAL NETWORKS THROUGH COMPUTATIONAL LINGUISTIC AND PSYCHOLINGUISTIC FEATURE MODELING

Abstract

Cybercriminals are increasingly using Internet-based text messaging applications to exploit their victims. Incidents of deceptive cybercrime in text-based communication are increasing and include fraud, scams, as well as favorable and unfavorable fake reviews. In this work, we use a text-based deception detection approach to train models for detecting text-based deceptive cybercrime in native and non-native English-speaking cybercriminal networks. I use both computational linguistic (CL) and psycholinguistic (PL) features for my models to study four types of deceptive text-based cybercrime: fraud, scams, favorable and unfavorable fake reviews. The data is obtained from three web genres namely: email, websites and social media.