***** To join INSNA, visit http://www.sfu.ca/~insna/ ***** We're also working on this extensively at the Media Lab as part of the Reality Mining project. Our system captures and analyzes each participantís audio, extracts keyword-based topic and context information, and uses waveform correlation / mutual information and 802.11b packet sniffing to establish the participantís location and the other users in local proximity. By next week weíll have 70 rigs comprised of a Sharp Zaurus PDA (running linux), headset microphone, 802.11b wireless CF card, and a 256 MB SD card. Profiles of a participantís typical social behavior are built over time by extracting conversation features such as speaking rate, energy, duration, participants, interruptions, transition probabilities, time spent holding the floor, popular topics, etc... Our website has some related papers along with my SunBelt presentation: http://reality.media.mit.edu/info.html Although Iíve spent the better part of the year getting the low-level speech feature extraction / PDA software to work correctly, the real goal is the analysis of the extremely rich social network dataset that the system enables. Weíve been using a variety of Bayesian network approaches (particularly variations on the coupled HMM), but they donít seem well suited to multi-relational data. Iím now starting to dabble with Probabilistic Relational Models. (Friedman et al. provide a good introduction to PRMs: http://citeseer.nj.nec.com/friedman99learning.html) Does anyone out there have experience/insight re: working with PRMs on social network data? cheers, -nathan. http://web.media.mit.edu/~nathan > >I was wondering if anyone was aware of any work done to record human >conversations (like at a conference) for SNA? I know there has been >work done analyzing videos, but I was looking for other approaches. > >Thanks! > >Alex Kilpatrick > _____________________________________________________________________ SOCNET is a service of INSNA, the professional association for social network researchers (http://www.sfu.ca/~insna/). To unsubscribe, send an email message to [log in to unmask] containing the line UNSUBSCRIBE SOCNET in the body of the message.