Abstract
Organizational members who conceal information about adverse behaviors present a substantial risk to that organization. Yet the task of identifying who is concealing information is extremely difficult, expensive, error-prone, and time-consuming. We propose a unique methodology for identifying concealed information: measuring people’s mouse-cursor movements in online screening questionnaires. We theoretically explain how mouse-cursor movements captured during a screening questionnaire differ between people concealing information and truth tellers. We empirically evaluate our hypotheses using an experiment during which people conceal information about a questionable act. While people completed the screening questionnaire, we simultaneously collected mouse-cursor movements and electrodermal activity-the primary sensor used for polygraph examinations-as an additional validation of our methodology. We found that mouse-cursor movements can significantly differentiate between people concealing information and people telling the truth. Mouse-cursor movements can also differentiate between people concealing information and truth tellers on a broader set of comparisons relative to electrodermal activity. Both mouse-cursor movements and electrodermal activity have the potential to identify concealed information, yet mouse-cursor movements yielded significantly fewer false positives. Our results demonstrate that analyzing mouse-cursor movements has promise for identifying concealed information. This methodology can be automated and deployed online for mass screening of individuals in a natural setting without the need for human facilitators. Our approach further demonstrates that mouse-cursor movements can provide insight into the cognitive state of computer users.
Original language | English (US) |
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Pages (from-to) | 1-32 |
Number of pages | 32 |
Journal | Journal of the Association for Information Systems |
Volume | 20 |
Issue number | 1 |
DOIs | |
State | Published - 2019 |
Keywords
- Concealed information
- Deception detection
- Electrodermal activity
- Graded-motor response analysis
- Mouse-cursor movement
- Video Emotion Analysis
ASJC Scopus subject areas
- Information Systems
- Computer Science Applications