OCTOPUS: An Online Topic-Aware Influence Analysis System for Social Networks

被引：11

作者：

Fan, Ju ^{[1
]}

Qiu, Jiarong ^{[1
]}

Li, Yuchen ^{[2
]}

Meng, Qingfei ^{[1
]}

Zhang, Dongxiang ^{[4
]}

Li, Guoliang ^{[5
]}

Tan, Kian-Lee ^{[3
]}

Du, Xiaoyong ^{[1
]}

机构：

[1] Renmin Univ China, Beijing, Peoples R China

[2] SMU, Singapore, Singapore

[3] NUS, Singapore, Singapore

[4] UESTC, Chengdu, Sichuan, Peoples R China

[5] Tsinghua Univ, Beijing, Peoples R China

来源：

2018 IEEE 34TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING (ICDE) | 2018年

关键词：

Influence Analysis; Social Networks; Topic-Aware; INFLUENCE MAXIMIZATION;

D O I：

10.1109/ICDE.2018.00178

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The wide adoption of social networks has brought a new demand on influence analysis. This paper presents OCTOPUS that offers social network users and analysts valuable insights through topic-aware social influence analysis services. OCTOPUS has the following novel features. First, OCTOPUS provides a user-friendly interface that allows users to employ simple and easy-to-use keywords to perform influence analysis. Second, OCTOPUS provides three powerful keyword-based topic-aware influence analysis tools: keyword-based influential user discovery, personalized influential keywords suggestion, and interactive influential paths exploration. These tools can not only discover influential users, but also provide insights on how the users influence the network. Third, OCTOPUS enables online influence analysis, which provides end-users with instant results. We have implemented and deployed OCTOPUS, and demonstrate its usability and efficiency on two social networks.

引用

页码：1569 / 1572

页数：4

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