Name
Abstract | ||
|---|---|---|
Microblog has become ubiquitous for social networking and information sharing. A few studies on information propagation over microblog reveal that the majority of users like to publish and share the news on microblog. The public opinion over the internet sometimes plays important role in national or international security. In this paper, we propose a new social network data model named Multi-Layer Network (MLN) over microblog. In the model, different layers represent different kinds of relationships between individuals. We present a new influence propagation model based on the MLN model. Finally, we conduct experiments on real-life microblog data of four recent hot topics. The experimental results show that our MLN model and influence propagation model are more effective in finding new and accurate active individuals comparing with the single layer data model and the linear threshold model. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/978-3-642-30428-6_5 | PAISI |
Keywords | Field | DocType |
single layer data model,real-life microblog data,information propagation,linear threshold model,new social network data,different kind,multi-layer network,different layer,new influence propagation model,mln model,propagation model | Data mining,Social media,Social network,Computer science,Microblogging,Knowledge extraction,Threshold model,Data model,Backbone network,Information sharing,The Internet | Conference |
Citations | PageRank | References |
4 | 0.41 | 13 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chao Li | 1 | 4 | 0.41 |
| Jun Luo | 2 | 222 | 26.61 |
| Joshua Zhexue Huang | 3 | 1365 | 82.64 |
| Jianping Fan | 4 | 2677 | 192.33 |