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| Content Provider | ACM Digital Library |
|---|---|
| Author | Wang, Zhu Zhang, Daqing Du, Rong Gu, Tao Xu, Huang Guo, Bin Yu, Zhiwen |
| Abstract | The newly emerging event-based social networks (EBSNs) extend social interaction from online to offline, providing an appealing platform for people to organize and participate realworld social events. In this paper, we investigate how to select potential participants in EBSNs from an event host's point of view. We formulate the problem as mining influential and preferable invitee set, considering from two complementary aspects. The first aspect concerns users' preference with respect to the event. The second aspect is influence maximization, which aims to influence the largest number of users to participate the event. In particular, we propose a novel Credit Distribution-User Influence Preference (CD-UIP) algorithm to find the most influential and preferable followers as the invitees. We collect a real-world dataset from a popular EBSNs called "Douban Events", and the experimental results on the dataset demonstrate the proposed algorithm outperforms the state-of-the-art prediction methods. |
| Starting Page | 879 |
| Ending Page | 883 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781450335744 |
| DOI | 10.1145/2750858.2805839 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2015-09-07 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Event-based social networks Influence maximization Invitee set Cd-uip User preference |
| Content Type | Text |
| Resource Type | Article |
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