Predictive Analytics
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Results for: Predictive Analytics
- Markowitz, David, and Jeremy Bailenson. “A Looking Glass into a Research Wonderland: 40 Years of Virtual Reality Scholarship Explicated via Natural Language Processing”, PsyArXiv Preprints. https://doi.org/10.31234/osf.io/2z5cj.
- Miller, M.R., F. Herrera, H. Jun, J.A. Landay, and J.N. Bailenson. “Personal Identifiability of User Tracking Data During Observation of 360-Degree VR Video”, Scientific Reports, 10 (2020). https://doi.org/10.1038/s41598-020-74486.
- Bailenson, J.N. “Protecting Nonverbal Data Tracked in Virtual Reality”, JAMA Pediatr.. https://doi.org/10.1001/jamapediatrics.2018.1909.
- Won, A., J. Bailenson, and J. Janssen. “Automatic Detection of Nonverbal Behavior Predicts Learning in Dyadic Interactions”, IEEE Transactions on Affective, 5, no. 2 (2014): 112-25.
- Won, A.S., J.N. Bailenson, S.C. Stathatos, and W. Dai. “Automatically Detected Nonverbal Behavior Predicts Creativity in Collaborating Dyads”, Journal of Nonverbal Behavior, 38, no. 3 (2014): 389-408.
- Won, A.S., L. Yu, J.H. Janssen, and J.N. Bailenson. “Tracking Gestures to Detect Gender”, Proceedings of the International Society for Presence Research Annual Conference.
- Jabon, M.E., S.J. Ahn, and J.N. Bailenson. “Automatically Analyzing Facial-Feature Movements to Identify Human Errors”, IEEE Journal of Intelligent Systems, 26, no. 2 (2011): 54-63.
- Jabon, M.E., J.N. Bailenson, E.D. Pontikakis, L. Takayama, and C. Nass. “Facial Expression Analysis for Predicting Unsafe Driving Behavior”, IEEE Pervasive Computing, 10, no. 4 (2011): 84-95.
- Ahn, S.J., J.N. Bailenson, J. Fox, and M.E. Jabon. “Using Automated Facial Expression Analysis for Emotion and Behavior Prediction”, Handbook of Emotions and Mass Media, 349-69.
- Jun, H., M. Miller, F. Herrera, B. Reeves, and J.N. Bailenson. “Stimulus Sampling With 360-Videos: Examining Head Movements, Arousal, Presence, Simulator Sickness, and Preference on a Large Sample of Participants and Videos”, IEEE Transactions on Affective Computing, 5, no. 2 (n.d.): 112-25.