Alex Pentland
ABSTRACT
Widespread adoption of interactive, peer-to-peer digital media will require a solution to the Privacy, Sharing, and Interest (PSI) problem: how can we know what the user wants to share with whom, and when, without burdening the user with constant updating of lists of approved users and sharing preferences? We argue that real-time analysis of user behavior provides an automatic PSI capability, allowing media to be automatically and proactively shared with a much lower user burden.
- Want, R., A. Hopper, et al. (1992). "The active badge location system." ACM Transactions on Information Systems (TOIS) 10(1): 91--102. Google Scholar
Digital Library
- Holmquist, L.E., J. Falk, et al. (1999). "Supporting Group Collaboration with Interpersonal Awareness Devices." Personal Technologies 3: 13--21.Google ScholarCross Ref
- Iwatani, Y. (1998). "Love: Japanese Style." Wired News 11.Google Scholar
- Terry, M., E.D. Mynatt, et al. (2002). "Social net: using patterns of physical proximity over time to infer shared interests." Conference on Human Factors in Computing Systems: 816--817. Google ScholarDigital Library
- Paulos, E. and E. Goodman (2004). "The familiar stranger: anxiety, comfort, and play in public places." Proceedings of the 2004 conference on Human factors in computing systems: 223--230. Google ScholarDigital Library
- Eagle, N., Pentland, A. (2003) Social Network Computing, Ubicomp 2003, Springer-Verlag Lecture Notes in Computer Science, No. 2864, pp. 289--296. See TR 570 1Google Scholar
- Eagle, N. and A. Pentland (2005). "Social serendipity: mobilizing social software." Pervasive Computing, IEEE 4(2): 28--34. See TR 580 Google ScholarDigital Library
- Davis, M., S. King, et al. (2004). "From context to content: leveraging context to infer media metadata." Proceedings of the 12th annual ACM international conference on Multimedia: 188--195. Google ScholarDigital Library
- Madan, A., Caneel, R., Pentland, A. (2005) "Voices of Attraction," AugCog Symposium of HCI 2005, Las Vegas, NV. See TR 584Google Scholar
- Gips, J., Pentland, A., "Mapping Human Networks," PerCom '06, Pisa, Italy, March 2006. See TR 586 Google ScholarDigital Library
- Gatica-Perez, D., I. McCowan, et al. "Detecting Group Interest Level in Meetings." Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP).Google Scholar
- Pentland, A. (2004) Social Dynamics: Signals and Behavior, Int'l Conf. On Developmental Learning, Salk Institute, San Diego, Oct. 20-22. See TR 579Google Scholar
- Pentland, A., (2005) Socially Aware Computation and Communication, IEEE Computer, March, pp. 63--70. See TR 590 Google ScholarDigital Library
- Eagle, N., and Pentland, A., "Eigenbehaviors: Identifying Structure in Routine, October 2005, See TR 601Google Scholar
- Pentland, A, Choudhury, T., Eagle, N., Push, S. (2005) Human Dynamics: Computation for Organizations, Pattern Recognition, vol 26, 503--511 See TR 589 Google ScholarDigital Library
- Dong, W., and Pentland, A., (2006) Multi-sensor data fusion using the influence model, IEEE Body Sensor Networks, April, Boston, MA. See TR 597Google Scholar
- Ambady, N., Rosenthal, R. (1992). Thin slices of expressive behavior as predictors of interpersonal consequences: A meta-analysis. Psychological Bulletin, 111(2), 256--274.Google ScholarCross Ref
- Gladwell, M. (2004) Blink. New York: Little BrownGoogle Scholar
- Madan, A., Pentland, A., (2006). Vibefones: Socially Aware Mobile Phones, ISWC06, Martingy Switzerland Oct. 11-15 See TR 602Google Scholar
Index Terms
- Human computing for interactive digital media
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