Name
Abstract | ||
|---|---|---|
Influence in Twitter has become recently a hotresearch topic since this micro-blogging service is widelyused to share and disseminate information. Some users aremore able than others to influence and persuade peers. Thus, studying most influential users leads to reach a largescaleinformation diffusion area, something very useful inmarketing or political campaigns. In this paper, we propose anew approach for influence assessment on Twitter network, itis based on a modified version of the conjunctive combinationrule in belief functions theory in order to combine differentinfluence markers such as retweets, mentions and replies. We experiment the proposed method on a large amount ofdata gathered from Twitter in the context of the EuropeanElections 2014 and deduce top influential candidates. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/SITIS.2015.82 | SITIS |
Keywords | Field | DocType |
Twitter network, Influence, Information fusion, Belief theory | Data science,Belief theory,World Wide Web,Computer science,Dissemination,Information fusion,Politics | Conference |
Citations | PageRank | References |
1 | 0.37 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lobna Azaza | 1 | 1 | 0.71 |
| Sergey Kirgizov | 2 | 1 | 0.37 |
| Marinette Savonnet | 3 | 24 | 16.76 |
| Eric Leclercq | 4 | 28 | 15.63 |
| Rim Faiz | 5 | 98 | 36.23 |