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The Language of Deception

Applying Findings on Opinion Spam to Legal and Forensic Discourses

Datos Bibliográficos

ID5900922
AutoresAlibek Jakupov (CY Cergy Paris Université), Julien Longhi (0000-0002-4134-9888, CY Cergy Paris Université), Besma Zeddini (0000-0002-4519-2996, CY Cergy Paris Université)
Año2023
Volumen9
Número1
Páginas10
Fecha de publicación2023-12-22
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaLanguages (JOURNAL)
Identificadores de la revistaISSN: 2226-471X • E-ISSN: 2226-471X
EditorialMDPI AG (PUBLISHER • IT)
DOI10.3390/languages9010010
OpenAlexW4390112341
IdiomaEN
Referencias citadas41

Digital forensic investigations are becoming increasingly crucial in criminal investigations and civil litigations, especially in cases of corporate espionage and intellectual property theft as more communication occurs online via e-mail and social media. Deceptive opinion spam analysis is an emerging field of research that aims to detect and identify fraudulent reviews, comments, and other forms of deceptive online content. In this paper, we explore how the findings from this field may be relevant to forensic investigation, particularly the features that capture stylistic patterns and sentiments, which are psychologically relevant aspects of truthful and deceptive language. To assess these features' utility, we demonstrate the potential of our proposed approach using the real-world dataset from the Enron Email Corpus. Our findings suggest that deceptive opinion spam analysis may be a valuable tool for forensic investigators and legal professionals looking to identify and analyze deceptive behavior in online communication. By incorporating these techniques into their investigative and legal strategies, professionals can improve the accuracy and reliability of their findings, leading to more effective and just outcomes

Computer security · Data science · Deception · Digital forensics · Espionage · Field (mathematics · Internet privacy · Lie detection · Political science · Public relations · Social media · World Wide Web · Authorship Attribution and Profiling · Computer Science · Law · Misinformation and Its Impacts · Psychology · Social Psychology · Spam and Phishing Detection

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