| Querying dynamic communities in online social networks简 |
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| 作者姓名： | Li WEIGANG Edans F. O. SANDES Jianya ZHENG Alba C. M. A. de MELO Lorna UDEN |
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| 基金项目： | Project supported by the Brazilian National Council for Scientific and Technological Development （CNPq） （No. 304058/2010-6） |
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| 摘 要： | Online social networks （OSNs） offer people the opportunity to join communities where they share a common interest or objective. This kind of community is useful for studying the human behavior, diffusion of information, and dynamics of groups. As the members of a community are always changing, an efficient solution is needed to query information in real time. This paper introduces the Follow Model to present the basic relationship between users in OSNs, and combines it with the MapReduce solution to develop new algorithms with parallel paradigms for querying. Two models for reverse relation and high-order relation of the users were implemented in the Hadoop system. Based on 75 GB message data and 26 GB relation network data from Twitter, a case study was realized using two dynamic discussion communities：#musicmonday and #beatcancer. The querying performance demonstrates that the new solution with the implementation in Hadoop significantly improves the ability to find useful information from OSNs.
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| 关 键 词： | Follow Model Hadoop MapReduce Querying Twitter |
Querying dynamic communities in online social networks |
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| Li WEIGANG,Edans F. O. SANDES,Jianya ZHENG,Alba C. M. A. de MELO,Lorna UDEN.Querying dynamic communities in online social networks[J].Journal of Zhejiang University-Science C(Computers and Electronics),2014,15(2):81-90. |
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| Authors: | Li Weigang Edans F O Sandes Jianya Zheng Alba C M A de Melo Lorna Uden |
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| Affiliation: | 1. Department of Computer Science, University of Brasilia, Brasilia, 70910-900, Brazil
2. School of Computing, Staffordshire University, Stafford, ST18 0AD, UK
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| Abstract: | Online social networks (OSNs) offer people the opportunity to join communities where they share a common interest or objective. This kind of community is useful for studying the human behavior, diffusion of information, and dynamics of groups. As the members of a community are always changing, an efficient solution is needed to query information in real time. This paper introduces the Follow Model to present the basic relationship between users in OSNs, and combines it with the MapReduce solution to develop new algorithms with parallel paradigms for querying. Two models for reverse relation and high-order relation of the users were implemented in the Hadoop system. Based on 75 GB message data and 26 GB relation network data from Twitter, a case study was realized using two dynamic discussion communities: #musicmonday and #beatcancer. The querying performance demonstrates that the new solution with the implementation in Hadoop significantly improves the ability to find useful information from OSNs. |
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| Keywords: | Follow Model Hadoop MapReduce Querying Twitter |
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