​Jinie Pak, PhD

Deception detection has been a long-standing concern of law-enforcement agencies, military, organizations, and individuals who are concerned about information quality and security.  My primary research goal aims to improve and develop deception detection techniques in computer mediated communication (CMC) through understanding of human behavior, and the design of intelligent technologies. In particular, I have researched two main non-verbal deception behaviors in CMC - social structural behavior and psychophysiological behavior. I have integrated advanced information technologies and traditional sociological and psychological theories and findings to create new possibilities that can make unique contributions to deception detection, computer-mediated communication, and human computer interaction research. 

 

I also have investigated psychophysiological behavior as a deception indicator using eye tracking technology. The empirical studies of eye movements have been largely ignored since the availability of eye movements in CMC is quite limited. I applied eye tracking technology to observe eye movement behaviors in online video chatting environment and innovatively operationalized eye gazing behaviors in terms of areas of interest (AOI) and conducted a lab-based experiment. The findings of the study can be applied to detecting deception in interpersonal chatting on social networking sites, in business communication (e.g. job interview and business collaboration), and in business-to-consumer communication. The study also can serve as an alternative method to polygraph test. Cyber security and credibility assessment have attracted a lot of attention from the government, research institutes, and industries in recent years. 

 

Currently I am looking into automatic detection of structural deception behavior in online communication, using natural language processing and machine learning techniques to effectively analyze raw data and information from diverse data source.