Influence Assessment in Twitter Multi-Relational Network
| Affiliation auteurs | !!!! Error affiliation !!!! |
| Titre | Influence Assessment in Twitter Multi-Relational Network |
| Type de publication | Conference Paper |
| Year of Publication | 2015 |
| Auteurs | Azaza L, Kirkizov S, Savonnet M, Leclercq E, Faiz R |
| Editor | Yetongnon K, Dipanda A |
| Conference Name | 2015 11TH INTERNATIONAL CONFERENCE ON SIGNAL-IMAGE TECHNOLOGY & INTERNET-BASED SYSTEMS (SITIS) |
| Publisher | Kasetsart University in Bangkok; LE2I (Laboratoire Electronique, Image et Informatique); University of Bourgogne; UKNOW; Center of Excellence for Unified Knowledge and Language Engineering at Kasetsart University.; IEEE Computer Society; IEEE Computer Soc |
| Conference Location | 345 E 47TH ST, NEW YORK, NY 10017 USA |
| ISBN Number | 978-1-4673-9721-6 |
| Mots-clés | Belief theory, Influence, Information fusion, Twitter network |
| Résumé | Influence in Twitter has become recently a hot research topic since this micro-blogging service is widely used to share and disseminate information. Some users are more able than others to influence and persuade peers. Thus, studying most influential users leads to reach a large-scale information diffusion area, something very useful in marketing or political campaigns. In this paper, we propose a new approach for influence assessment on Twitter network, it is based on a modified version of the conjunctive combination rule in belief functions theory in order to combine different influence markers such as retweets, mentions and replies. We experiment the proposed method on a large amount of data gathered from Twitter in the context of the European Elections 2014 and deduce top influential candidates. |
| DOI | 10.1109/SITIS.2015.82 |