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| Content Provider | ACM Digital Library |
|---|---|
| Author | Ji, Wenqian Fang, Zhipeng Chen, Tianjian Li, Xuan Tang, Yan Ma, Pengju Tang, Shijie |
| Abstract | Social network is rapidly growing to be a major platform for the dissemination of breaking events. Numerous studies focus on the user's influence in different types of social network and visualize user and event propagation process. However, little works is done to visualize and analyze the social influence of breaking events. To fill this gap, we propose VIBES, a hybrid model that combines both event popularity and event public attention to quantitatively measure and visualize event social influence through time at both macroscopic and microscopic levels. Experimental results based on two real-world event datasets from Weibo validate the effectiveness of VIBES for accurately capturing breaking sub-events as well as visualizing event social influence from different temporal granularity. The visualization results produced by VIBES are not only useful for public users to have a better understanding of breaking events, but also helpful for mass media and and government agencies to mediate and stabilize the outbreak of event. |
| Starting Page | 117 |
| Ending Page | 121 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781450341493 |
| DOI | 10.1145/2968220.2968246 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2016-09-24 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Information visualization Event social influence Social network Hybrid model |
| Content Type | Text |
| Resource Type | Article |
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