SENTIMENT AND BEHAVIORAL ANALYSIS IN EDISCOVERY

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dc.contributor.advisorNarasimha K. Shashidhar, PhD
dc.contributor.committeeMemberCihan Varol, PhD
dc.contributor.committeeMemberABM Rezbaul Islam, PhD
dc.creatorKrishnan, Sundar
dc.creator.orcid0000-0003-4360-1300
dc.date.accessioned2022-08-24T18:06:33Z
dc.date.available2022-08-24T18:06:33Z
dc.date.created2022-08
dc.date.issued2022-08-01T05:00:00.000Z
dc.date.submittedAugust 2022
dc.date.updated2022-08-24T18:06:34Z
dc.description.abstractA suspect or person-of-interest during legal case review or forensic evidence review can exhibit signs of their individual personality through the digital evidence collected for the case. Such personality traits of interest can be analytically harvested for case investigators or case reviewers. However, manual review of evidence for such flags can take time and contribute to increased costs. This study focuses on certain use-case scenarios of behavior and sentiment analysis as a critical requirement for a legal case’s success. This study aims to quicken the review and analysis phase and offers a software prototype as a proof-of-concept. The study starts with the build and storage of Electronic Stored Information (ESI) datasets for three separate fictitious legal cases using publicly available data such as emails, Facebook posts, tweets, text messages and a few custom MS Word documents. The next step of this study leverages statistical algorithms and automation to propose approaches towards identifying human sentiments, behavior such as, evidence of financial fraud behavior, and evidence of sexual harassment behavior of a suspect or person-of-interest from the case ESI. The last stage of the study automates these approaches via a custom software and presents a user interface for eDiscovery teams and digital forensic investigators.
dc.format.mimetypeapplication/pdf
dc.identifier.uri
dc.identifier.urihttps://hdl.handle.net/20.500.11875/3613
dc.language.isoEnglish
dc.subjectDigital forensics
dc.subjectForensic evidence data mining
dc.titleSENTIMENT AND BEHAVIORAL ANALYSIS IN EDISCOVERY
dc.typeThesis
dc.type.materialtext
thesis.degree.collegeCollege of Science and Engineering Technology
thesis.degree.departmentComputer Science
thesis.degree.disciplineDigital and Cyber Forensic Science
thesis.degree.grantorSam Houston State University
thesis.degree.nameDoctor of Philosophy

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