Computer-Mediated Deception: Strategies Revealed by Language-Action Cues in Spontaneous Communication

Abstract

Computer-mediated deception threatens the security of online users’ private and personal information. Previous research confirms that humans are bad lie detectors, while demonstrating that certain observable linguistic features can provide crucial cues to detect deception. We designed and conducted an experiment that creates spontaneous deception scenarios in an interactive online game environment. Logistic regression, and certain classification methodologies were applied to analyzing data collected during fall 2014 through spring 2015. Our findings suggest that certain language-action cues (e.g., cognitive load, affective process, latency, and wordiness) reveal patterns of information behavior manifested by deceivers in spontaneous online communication. Moreover, computational approaches to analyzing these language-action cues can provide significant accuracy in detecting computer-mediated deception.

Key words and phrases:

• computer-mediated communication
• computer-mediated deception
• deception detection
• deceptive communications
• human–computer interaction
• interpersonal deception theory
• language-action cues

Acknowledgments

The authors appreciate advice from Mike Burmester, and acknowledge the game development, data collection, and analysis efforts of Muye Liu, Shashanka S. Timmarajus, Kashyap Vemuri, Hengyi Fu, Laura Clark, Aravind Hariharan, and many research participants from Florida State University.

Funding

The authors wish to thank the National Science Foundation EAGER grants #1347113 and #1347120, 09/01/13–08/31/15, the Florida Center for Cybersecurity Collaborative Seed Grant 03/01/15–02/28/16, and the Florida State University Council for Research and Creativity Planning Grant #034138, 12/01/13–12/12/14.

Notes

1. With the exception of this paragraph, which specifically discusses “immediacy” and its converse, “nonimmediacy,” the balance of the discussion will simply refer to the general/broad concept of immediacy, as encompassing behaviors that create either psychological closeness (i.e., immediacy behaviors) or psychological distance (nonimmediacy behaviors).

2. These strategies include (1) uncertainty and vagueness, (2) nonimmediacy, reticence, and withdrawal, (3) disassociation, and (4) image- and relationship-protecting behavior.

3. Words categorized or classified as relating to the “social” category in LIWC include words such as “family,” “friends,” and “humans.”

Additional information

Funding

The authors wish to thank the National Science Foundation EAGER grants #1347113 and #1347120, 09/01/13–08/31/15, the Florida Center for Cybersecurity Collaborative Seed Grant 03/01/15–02/28/16, and the Florida State University Council for Research and Creativity Planning Grant #034138, 12/01/13–12/12/14.

Notes on contributors

Shuyuan Mary Ho

Shuyuan Mary Ho ([email protected]; corresponding author) is an assistant professor at the College of Communication and Information, Florida State University. Her research focuses on trusted human–computer interactions, specifically addressing issues of cyber insider threats and online deception. Her research has been funded by the U.S. National Science Foundation, Florida Center for Cybersecurity, and the Florida State University Council of Research and Creativity Her work appears in Journal of Management Information Systems, Journal of the American Society for Information Science and Technology, Information Systems Frontiers, Information Processing & Management, as well as IEEE and ACM Conference Proceedings.

Jeffrey T. Hancock

Jeffrey T. Hancock ([email protected]) is a professor of in the Department of Communication at Stanford University. He works on understanding psychological and interpersonal processes in social media by using computational linguistics and behavioral experiments to examine deception and trust, emotional dynamics, intimacy and relationships, and social support. His research has been published in over eighty journal articles and conference proceedings, and has been supported by funding from the U.S. National Science Foundation and U.S. Department of Defense. His work has also been featured in the popular press, including the New York Times, CNN, NPR, CBS, and the BBC.

Cheryl Booth

Cheryl Booth ([email protected]) is a doctoral candidate in the School of Information, Florida State University. She earned a JD from the Valparaiso (Indiana) University School of Law. She is a licensed attorney in the state of Massachusetts. Her primary research interest is in the national and international information policies vis-à-vis information privacy and data security, with an emphasis on the potential impact of different policies on information behaviors.

Xiuwen Liu

Xiuwen Liu ([email protected]) is a professor of computer science at Florida State University. His research interests include modeling high dimensional spatial-temporal data in different domains and identifying intrinsic patterns with applications in cyber security, remote sensing, image and video analysis, computational biology, and machine learning. His research has been published in IEEE Transactions on Pattern Recognition and Machine Intelligence, IEEE Transactions on Neural Networks, and IEEE Transactions on Image Processing.