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 booklet constitutes the completely refereed complaints of the overseas 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 overseas 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 offered have been rigorously reviewed and chosen from fifty eight submissions. The papers learn quite a lot of thoughts and techniques 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
Social consensus through the influence of committed minorities. Physical Review E 84(1), 011130 (2011) 8. : In-depth Behavior Understanding and Use: the Behavior Informatics Approach. Information Science 180(17), 3067–3085 (2010) 9. : Cascading behavior in networks: Algorithmic and economic issues. Algorithmic Game Theory 24, 613–632 (2007) 10. : Threshold models of collective behavior. American Journal of Sociology, 1420–1443 (1978) 11. com Abstract. Mobile phone data record people’s calling logs in everyday life, which reflecting their custom, pattern and lifestyle.
Kearns’s team did in their experiments , we also gave all subjectss an after experiment survey in which w they were invited to comment on strategies of theemselves and others’ they obsserved during the experiment. Out of 36 survey tables,, 31 were submitted after experriment. Twenty-three subjects chose the color with higgher score originally. Four subjeects made choice according to the degree of themselves and others. One subject referred d he made choice considered the degree as well as the m majority color of the last expeeriments.
The steps are tag identification, tag merge and tag deletion. Tag Identification. e. region ID, base station ID, tag Using Mobile Phone Location Data for Urban Activity Analysis 33 value and number of occurrences. When time elapses, location may vary. When a new location appears, it will be tagged in sequence and stored in the database. tag is set to 1. If the next occurrence of location has been already existed in the database, num will add 1. Tag Merge. Mobile phone data are generally located by base station.