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

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dc.contributor.advisorJones, James H
dc.contributor.authorMbaziira, Alex Vincent
dc.creatorMbaziira, Alex Vincent
dc.date.accessioned2018-10-22T01:21:16Z
dc.date.available2018-10-22T01:21:16Z
dc.date.issued2017
dc.description.abstractCybercriminals 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.
dc.format.extent115 pages
dc.identifier.urihttps://hdl.handle.net/1920/11304
dc.language.isoen
dc.rightsCopyright 2017 Alex Vincent Mbaziira
dc.subjectInformation technology
dc.subjectComputational linguistics
dc.subjectCybercrime
dc.subjectDeception
dc.subjectMachine learning
dc.subjectPsycholinguistics
dc.titleDETECTING AND ANALYZING CYBERCRIME IN TEXT-BASED COMMUNICATION OF CYBERCRIMINAL NETWORKS THROUGH COMPUTATIONAL LINGUISTIC AND PSYCHOLINGUISTIC FEATURE MODELING
dc.typeDissertation
thesis.degree.disciplineInformation Technology
thesis.degree.grantorGeorge Mason University
thesis.degree.levelPh.D.

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