Analyzing, Modeling, and Simulation for Human Dynamics in Social Network
This paper studies the human behavior in the top-one social network system in China (Sina Microblog system). By analyzing real-life data at a large scale, we find that the message releasing interval (intermessage time) obeys power law distribution both at individual level and at group level. Statist...
Saved in:
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2012-01-01
|
| Series: | Abstract and Applied Analysis |
| Online Access: | http://dx.doi.org/10.1155/2012/208791 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832549430868312064 |
|---|---|
| author | Yunpeng Xiao Bai Wang Yanbing Liu Zhixian Yan Xian Chen Bin Wu Guangxia Xu Yuanni Liu |
| author_facet | Yunpeng Xiao Bai Wang Yanbing Liu Zhixian Yan Xian Chen Bin Wu Guangxia Xu Yuanni Liu |
| author_sort | Yunpeng Xiao |
| collection | DOAJ |
| description | This paper studies the human behavior in the top-one social network system in China (Sina Microblog system). By analyzing real-life data at a large scale, we find that the message releasing interval (intermessage time) obeys power law distribution both at individual level and at group level. Statistical analysis also reveals that human behavior in social network is mainly driven by four basic elements: social pressure, social identity, social participation, and social relation between individuals. Empirical results present the four elements' impact on the human behavior and the relation between these elements. To further understand the mechanism of such dynamic phenomena, a hybrid human dynamic model which combines “interest” of individual and “interaction” among people is introduced, incorporating the four elements simultaneously. To provide a solid evaluation, we simulate both two-agent and multiagent interactions with real-life social network topology. We achieve the consistent results between empirical studies and the simulations. The model can provide a good understanding of human dynamics in social network. |
| format | Article |
| id | doaj-art-394cf17a45b74a8ba2f37a915da26035 |
| institution | Kabale University |
| issn | 1085-3375 1687-0409 |
| language | English |
| publishDate | 2012-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Abstract and Applied Analysis |
| spelling | doaj-art-394cf17a45b74a8ba2f37a915da260352025-02-03T06:11:20ZengWileyAbstract and Applied Analysis1085-33751687-04092012-01-01201210.1155/2012/208791208791Analyzing, Modeling, and Simulation for Human Dynamics in Social NetworkYunpeng Xiao0Bai Wang1Yanbing Liu2Zhixian Yan3Xian Chen4Bin Wu5Guangxia Xu6Yuanni Liu7Beijing 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, ChinaChongqing Engineering Laboratory of Internet and Information Security, Chongqing University of Posts and Telecommunications (CQUPT), no. 2 Chongwen Road, Nanan District, Chongqing 400065, ChinaSamsung Research, San Jose, CA, USAWeb Intelligence Laboratory, Konkuk University, Seoul, Republic of KoreaBeijing Key Laboratory of Intelligent Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications (BUPT), Beijing, ChinaChongqing Engineering Laboratory of Internet and Information Security, Chongqing University of Posts and Telecommunications (CQUPT), no. 2 Chongwen Road, Nanan District, Chongqing 400065, ChinaChongqing Engineering Laboratory of Internet and Information Security, Chongqing University of Posts and Telecommunications (CQUPT), no. 2 Chongwen Road, Nanan District, Chongqing 400065, ChinaThis paper studies the human behavior in the top-one social network system in China (Sina Microblog system). By analyzing real-life data at a large scale, we find that the message releasing interval (intermessage time) obeys power law distribution both at individual level and at group level. Statistical analysis also reveals that human behavior in social network is mainly driven by four basic elements: social pressure, social identity, social participation, and social relation between individuals. Empirical results present the four elements' impact on the human behavior and the relation between these elements. To further understand the mechanism of such dynamic phenomena, a hybrid human dynamic model which combines “interest” of individual and “interaction” among people is introduced, incorporating the four elements simultaneously. To provide a solid evaluation, we simulate both two-agent and multiagent interactions with real-life social network topology. We achieve the consistent results between empirical studies and the simulations. The model can provide a good understanding of human dynamics in social network.http://dx.doi.org/10.1155/2012/208791 |
| spellingShingle | Yunpeng Xiao Bai Wang Yanbing Liu Zhixian Yan Xian Chen Bin Wu Guangxia Xu Yuanni Liu Analyzing, Modeling, and Simulation for Human Dynamics in Social Network Abstract and Applied Analysis |
| title | Analyzing, Modeling, and Simulation for Human Dynamics in Social Network |
| title_full | Analyzing, Modeling, and Simulation for Human Dynamics in Social Network |
| title_fullStr | Analyzing, Modeling, and Simulation for Human Dynamics in Social Network |
| title_full_unstemmed | Analyzing, Modeling, and Simulation for Human Dynamics in Social Network |
| title_short | Analyzing, Modeling, and Simulation for Human Dynamics in Social Network |
| title_sort | analyzing modeling and simulation for human dynamics in social network |
| url | http://dx.doi.org/10.1155/2012/208791 |
| work_keys_str_mv | AT yunpengxiao analyzingmodelingandsimulationforhumandynamicsinsocialnetwork AT baiwang analyzingmodelingandsimulationforhumandynamicsinsocialnetwork AT yanbingliu analyzingmodelingandsimulationforhumandynamicsinsocialnetwork AT zhixianyan analyzingmodelingandsimulationforhumandynamicsinsocialnetwork AT xianchen analyzingmodelingandsimulationforhumandynamicsinsocialnetwork AT binwu analyzingmodelingandsimulationforhumandynamicsinsocialnetwork AT guangxiaxu analyzingmodelingandsimulationforhumandynamicsinsocialnetwork AT yuanniliu analyzingmodelingandsimulationforhumandynamicsinsocialnetwork |