Deception Detection: An Exploration of Annotated Text-Based Cues

dc.contributor.author McHaney, Roger
dc.contributor.author George, Joey
dc.contributor.author Gupta, Manjul
dc.contributor.department Supply Chain Management
dc.date 2020-02-10T16:00:37.000
dc.date.accessioned 2020-07-02T06:25:18Z
dc.date.available 2020-07-02T06:25:18Z
dc.date.copyright Mon Jan 01 00:00:00 UTC 2018
dc.date.issued 2018-01-01
dc.description.abstract <p>Do embedded textual cues in asynchronous communication affect deceptive message detection? The expanded use of social media and rich media applications in business make this an important issue. Prior research indicates deception commonly occurs in all forms of communication and people have difficulty detecting its use. Asynchronous online communications are no exception and offer users a variety of media choices which may complicate deception detection, particularly if the sender has strategically selected a channel intended to disguise their intentions. The current study investigated whether embedded, non-verbal cues in common media forms found in asynchronous online venues influenced deception detection. Drawing on media synchronicity theory, results suggest embedding non-verbal cues in the form of annotated text can enhance deception detection. Overall, the findings suggest managers must be wary of sender motivations, which can influence message veracity, particularly in low synchronicity environments where media is subject to edits and manipulations.</p>
dc.description.comments <p>This accepted article is published as McHaney, Roger; George, Joey F.; and Gupta, Manjul (2018) "Deception Detection: An Exploration of Annotated Text-Based Cues," Journal of the Midwest Association for Information Systems (JMWAIS): Vol. 2018 : Iss. 2 , Article 2. DOI: <a target="_blank">10.17705/3jmwa.000041</a> Available at: http://aisel.aisnet.org/jmwais/vol2018/iss2/2</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/scm_pubs/70/
dc.identifier.articleid 1068
dc.identifier.contextkey 16497766
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath scm_pubs/70
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/84615
dc.language.iso en
dc.source.uri https://aisel.aisnet.org/cgi/viewcontent.cgi?article=1046&context=jmwais
dc.subject.disciplines Business Analytics
dc.subject.disciplines Business and Corporate Communications
dc.subject.disciplines Communication Technology and New Media
dc.subject.disciplines Operations and Supply Chain Management
dc.subject.disciplines Technology and Innovation
dc.subject.keywords media synchronicity theory
dc.subject.keywords annotated text
dc.subject.keywords deception detection
dc.subject.keywords deceptive communication
dc.subject.keywords paralanguage
dc.subject.keywords computer-mediated communication
dc.subject.keywords social media
dc.title Deception Detection: An Exploration of Annotated Text-Based Cues
dc.type article
dc.type.genre article
dspace.entity.type Publication
relation.isAuthorOfPublication fccb24a5-70bf-4fe4-bc21-a35670de9de5
relation.isOrgUnitOfPublication ef3ab1b0-d571-4148-84dd-470ef1cdb17a
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