DOBNet: exploiting the discourse of deception behaviour to uncover online deception strategies

Abstract

Online deception is fuelled by the escalated penetration of the Internet and social media. As the threat of online deception increases, understanding deception behaviour and underlying strategies is having a greater social impact. The verbal behaviour of online deception has recently been extended to the discourse level; nevertheless, discourse behaviours have been examined in isolation without referring to other behaviours in the discourse. By conceptualising the discourse of online behaviour as a social network (DOBNet), this research investigates possible impacts of deception intent on the central structures of DOBNet at three different levels: the discourse behaviour, subnetwork, and whole network. The empirical results of discourse network analysis and statistical tests provide partial support for each of the hypothesised effects. The findings not only demonstrate the efficacy of discourse in distinguishing deceivers from truth-tellers but also extend deception theories by confirming deception strategies from the perspective of discourse network and by uncovering unique characteristics of online deception strategies.

Keywords:

• deception detection
• discourse
• discourse behaviour
• discourse network analysis

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported in part by the National Science Foundation [grant number IIS-1250395], the Youth Scientific Foundation of Southwestern University of Finance and Economics [grant number JBK150133] and the Natural Science Joint Foundation of Guizhou Province of China [grant number LKG[2013]45]. Any opinions, findings or recommendations expressed here are those of the authors and are not necessarily those of the sponsors of this research.