A Hybrid Human Dynamics Model on Analyzing Hotspots in Social Networks
The increasing development of social networks provides a unique source for analyzing human dynamics in the modern age. In this paper, we analyze the top-one Internet forum in China (“Tianya Club”) and identify the statistical properties of hotspots, which can promptly reflect the crowd events in peo...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2012-01-01
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| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/2012/678286 |
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| _version_ | 1832564304388292608 |
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| author | Yunpeng Xiao Bai Wang Bin Wu Zhixian Yan Shousheng Jia Yanbing Liu |
| author_facet | Yunpeng Xiao Bai Wang Bin Wu Zhixian Yan Shousheng Jia Yanbing Liu |
| author_sort | Yunpeng Xiao |
| collection | DOAJ |
| description | The increasing development of social networks provides a unique source
for analyzing human dynamics in the modern age. In this paper, we analyze
the top-one Internet forum in China (“Tianya Club”) and identify the statistical properties of hotspots, which can promptly reflect the crowd events
in people's real-life. Empirical observations indicate that the interhotspot
distribution follows a power law. To further understand the mechanism of
such dynamic phenomena, we propose a hybrid human dynamic model that
combines “memory” of individual and “interaction” among people. To build
a rich simulation and evaluate this hybrid model, we apply three different
network datasets (i.e., WS network, BA network, and Karate-Club). Our
simulation results are consistent with the empirical studies, which indicate
that the model can provide a good understanding of the dynamic mechanism
of crowd events using such social networking data. We additionally analyze
the sensitivity of model parameters and find the optimal model settings. |
| format | Article |
| id | doaj-art-fc286c8bf6294de5adad3550257c75de |
| institution | Kabale University |
| issn | 1026-0226 1607-887X |
| language | English |
| publishDate | 2012-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Discrete Dynamics in Nature and Society |
| spelling | doaj-art-fc286c8bf6294de5adad3550257c75de2025-02-03T01:11:21ZengWileyDiscrete Dynamics in Nature and Society1026-02261607-887X2012-01-01201210.1155/2012/678286678286A Hybrid Human Dynamics Model on Analyzing Hotspots in Social NetworksYunpeng Xiao0Bai Wang1Bin Wu2Zhixian Yan3Shousheng Jia4Yanbing Liu5Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications (BUPT), Beijing, ChinaBeijing Key Laboratory of Intelligent Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications (BUPT), Beijing, ChinaBeijing Key Laboratory of Intelligent Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications (BUPT), Beijing, ChinaSchool of Computer and Communication Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, SwitzerlandChongqing Engineering Laboratory of Internet and Information Security, Chongqing University of Posts and Telecommunications (CQUPT), Room 4029, No. 2 Chongwen Road, Nanan District, Chongqing 400065, ChinaChongqing Engineering Laboratory of Internet and Information Security, Chongqing University of Posts and Telecommunications (CQUPT), Room 4029, No. 2 Chongwen Road, Nanan District, Chongqing 400065, ChinaThe increasing development of social networks provides a unique source for analyzing human dynamics in the modern age. In this paper, we analyze the top-one Internet forum in China (“Tianya Club”) and identify the statistical properties of hotspots, which can promptly reflect the crowd events in people's real-life. Empirical observations indicate that the interhotspot distribution follows a power law. To further understand the mechanism of such dynamic phenomena, we propose a hybrid human dynamic model that combines “memory” of individual and “interaction” among people. To build a rich simulation and evaluate this hybrid model, we apply three different network datasets (i.e., WS network, BA network, and Karate-Club). Our simulation results are consistent with the empirical studies, which indicate that the model can provide a good understanding of the dynamic mechanism of crowd events using such social networking data. We additionally analyze the sensitivity of model parameters and find the optimal model settings.http://dx.doi.org/10.1155/2012/678286 |
| spellingShingle | Yunpeng Xiao Bai Wang Bin Wu Zhixian Yan Shousheng Jia Yanbing Liu A Hybrid Human Dynamics Model on Analyzing Hotspots in Social Networks Discrete Dynamics in Nature and Society |
| title | A Hybrid Human Dynamics Model on Analyzing Hotspots in Social Networks |
| title_full | A Hybrid Human Dynamics Model on Analyzing Hotspots in Social Networks |
| title_fullStr | A Hybrid Human Dynamics Model on Analyzing Hotspots in Social Networks |
| title_full_unstemmed | A Hybrid Human Dynamics Model on Analyzing Hotspots in Social Networks |
| title_short | A Hybrid Human Dynamics Model on Analyzing Hotspots in Social Networks |
| title_sort | hybrid human dynamics model on analyzing hotspots in social networks |
| url | http://dx.doi.org/10.1155/2012/678286 |
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