| 社交网Twitter平台的人物关系网社区发现 |
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| 引用本文： | 钟玲,林柏钢.社交网Twitter平台的人物关系网社区发现[J].信息网络安全,2014(5):32-36. |
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| 作者姓名： | 钟玲 林柏钢 |
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| 作者单位： | [1]福州大学数学与计算机科学学院,福建福州350108; [2]网络系统信息安全福建省高校重点实验室,福建福州350108 |
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| 基金项目： | 福建省科技厅重点资助项目[2012H0025]、福建省安全课题资助项目[822711] |
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| 摘 要： | 社交网络服务（social networking service，SNS）已融入到大众生活中。人们将自己的信息上传到网络中，并通过社交网站管理自己的社交圈子，由此造成大量的个人信息在社交网络上被公开。文章基于Twitter平台，设计实现了Twitter用户关系网的社区发现。通过实时采集Twitter用户信息，重建人物关系网，改进Newman快速算法划分社区发现人物关系网。文章通过可视化的界面呈现用户的社区关系，提供用户网络行为，为决策者的舆情监控或个性推荐提供了参考凭据。
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| 关 键 词： | Twitter 社交网络 社区发现 Newman快速算法 |
Finding Community Structures of Users＇ Relationships in Twitter |
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| Affiliation: | ZHONG Ling , LIN Bo-gang (1.College of Mathematics and Computer Science in Fuzhou University, Fuzhou Fujian 350108, China; 2.Key Lab of Information Security of Network System in Fujian Province, Fuzhou Fujian 350108, China) |
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| Abstract: | SNS （social networking service） has been integrated into public life. People upload their own information to the network and use the social networking sites to manage their social relationship. A large number of personal information is presented on social networks. Based on the Twitter platform, this paper designs to find community structure of Twitter users. With the real-time information collecting, this paper rebuilds the relationships of users, improving Fast- Newman algorithms in dividing social networks. The paper uses a visualization system to automatically visualizing community structures, providing decision makers with user network behavior to implement personalized recommendation. |
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| Keywords: | Twitter social networking community mining Fast-Newman algorithm |
| 本文献已被 CNKI 维普 等数据库收录！ |
