Bridging the Gap for Online Deception Detection: Uncovering Methodology to Identify Deceptive Content in Mediated Communication

Abstract

Detecting deception online and in mediated communication is complex and has gained recognition due to misinformation. Traditionally most deception detection in communication relies on analysing nonverbal cues in body language and facial expression; mediated communication prohibits many of these cues from influencing the interpretation of message meaning. Given the ability for deceptive information to thrive online it becomes necessary to develop an effective method for digital deception data analysis. A method called Statement Analysis (SA) is commonly utilized in law enforcement and may be suitable for use as is or with modifications in mediated communication research. The goals of our ongoing research on mediated deception are three-fold: (1) uncover observations about mediated deception, specifically in social media posts from our current exploratory study, (2) to test and modify the current SA methodology within our current study for use and application within mediated communication contexts, and (3) to develop a textual deception detection methodology to apply within mediated communication. The findings of this exploratory research are presented within the content of examples that may be relevant to the creation and distribution of crisis messages, as the dissemination of misinformation in crisis events may be particularly critical.