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Untangling a web of lies: Exploring automated detection of deception in computer-mediated communication

Ludwig, S., van Laer, T., de Ruyter, K. & Friedman, M. (2016). Untangling a web of lies: Exploring automated detection of deception in computer-mediated communication. Journal of Management Information Systems, 33(2), pp. 511-541. doi: 10.1080/07421222.2016.1205927


Safeguarding organizations against opportunism and severe deception in computer-mediated communication (CMC) presents a major challenge to CIOs and IT managers. New insights into linguistic cues of deception derive from the speech acts innate to CMC. Applying automated text analysis to archival email exchanges in a CMC system as part of a reward program, we assess the ability of word use (micro-level), message development (macrolevel), and intertextual exchange cues (meta-level) to detect severe deception by business partners. We empirically assess the predictive ability of our framework using an ordinal multilevel regression model. Results indicate that deceivers minimize the use of referencing and self-deprecation but include more superfluous descriptions and flattery. Deceitful channel partners also over structure their arguments and rapidly mimic the linguistic style of the account manager across dyadic e-mail exchanges. Thanks to its diagnostic value, the proposed framework can support firms’ decision-making and guide compliance monitoring system development.

Publication Type: Article
Additional Information: This is an Accepted Manuscript of an article to be published by Taylor & Francis in Journal of Management Information Systems and to be available online at
Publisher Keywords: CMC between business partners, deception severity, speech act theory, automated text analysis
Subjects: H Social Sciences > HD Industries. Land use. Labor
Departments: Bayes Business School > Management
Text - Accepted Version
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