Download Behavior and Social Computing: International Workshop on by Ma Zhixin, Xu Yusheng, Tharam S. Dillon (auth.), Longbing PDF

By Ma Zhixin, Xu Yusheng, Tharam S. Dillon (auth.), Longbing Cao, Hiroshi Motoda, Jaideep Srivastava, Ee-Peng Lim, Irwin King, Philip S. Yu, Wolfgang Nejdl, Guandong Xu, Gang Li, Ya Zhang (eds.)

This ebook constitutes the completely refereed complaints of the foreign Workshops on habit and Social Informatics and Computing, BSIC 2013, held as collocated occasion of IJCAI 2013, in Beijing, China in August 2013 and the foreign Workshop on habit and Social Informatics, BSI 2013, held as satellite tv for pc workshop of PAKDD 2013, in Gold Coast, Australia, in April 2013. The 23 papers awarded have been conscientiously reviewed and chosen from fifty eight submissions. The papers learn a variety of recommendations and strategies for behavior/social-oriented analyses together with behavioral and social interplay and community, behavioral/social styles, behavioral/social affects, the formation of behavioral/social-oriented teams and collective intelligence and behavioral/social intelligence emergence.

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Extra info for Behavior and Social Computing: International Workshop on Behavior and Social Informatics, BSI 2013, Gold Coast, QLD, Australia, April 14-17, 2013 and International Workshop on Behavior and Social Informatics and Computing, BSIC 2013, Beijing, China, Augus

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2) Time length of staying at different locations for each person is quite different. User p2 stays at home for up to 18 36 R. Xie, H. Xu, and Y. Yue hours, but 4 hours in workplace. It is opposite that user p3 at home for 9 hours, but 10 hours for workplace. 3) There is very different of staying frequency in different locations. By enlarging time interval from 1 hour to 4 hours, we can get active matrix shown in Table 2, here 0 for home and 1 for workplace. Table 2. Datamation of users’ location p1 p2 p3 0 0 0 0 1 0 1 0 1 1 0 1 0 0 1 0 0 0 From Table 2, activities of user p1 are regular, showing a symmetrical structure.

There were twenty subjects claimed that they did adopt stubborn strategy. Two T subjects did perform stubborn originally but folllow others in the later games. One O ranked 26 among all 36 subjects, so he may not connsist this strategy during the expeeriment. Fig. 4. Visualization of the “random “ observer” method for detecting meaningful variationn in subject behavior. (Left) Empirrical cumulative distribution function(CDF) of total player weealth (blue), in which wealth (x axiss) is plotted against the fraction of the 36 subjects earning at lleast that amount (y axis).

So, there may have two base stations alternately in the record in a short time period. We call it shocking pair. As interval of each concussion is only a few seconds, and the original value is returned after a few seconds, such phenomenon is obvious and easy to identify. We can detect shocking pair as follows. Set time threshold as T and frequency threshold as N. If the number of occurrences of two locations is more than N at time T, then determine these two locations as a shocking pair. For example, if there is a sequence {A, B, A, C, A, B} at T=30 seconds and N=2, the frequency of A and B exceeds N, then A and B is a shocking pair.

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