Name
Abstract | ||
|---|---|---|
In micro-blogging, people talk about their daily life and change minds freely, thus by mining people's interest in micro-blogging, we will easily perceive the pulse of society. In this paper, we catch what people are caring about in their daily life by discovering meaningful communities based on probabilistic factor model (PFM). The proposed solution identifies people's interest from their friendship and content information. Therefore, it reveals the behaviors of people in micro-blogging naturally. Experimental results verify the effectiveness of the proposed model and show people's social life vividly. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1145/2187980.2188099 | WWW (Companion Volume) |
Keywords | Field | DocType |
change mind,show people,proposed solution,social life,content information,mining people,daily life,probabilistic factor model,micro blogging,factor model | World Wide Web,Social media,Friendship,Computer science,Microblogging,Probabilistic logic | Conference |
Citations | PageRank | References |
0 | 0.34 | 4 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Heng Gao | 1 | 41 | 2.15 |
| Qiudan Li | 2 | 440 | 28.06 |
| Hongyun Bao | 3 | 48 | 4.23 |
| Shuangyong Song | 4 | 72 | 4.34 |