%0 Conference Proceedings %T Influence Assessment in Twitter Multi-Relational Network %+ Laboratoire Electronique, Informatique et Image [UMR6306] (Le2i) %+ Laboratoire de Recherche Opérationnelle de Décision et de Contrôle de Processus (LARODEC) %A Azaza, Lobna %A Kirkizov,, Sergey %A Savonnet, Marinette %A Leclercq, Eric %A Faiz, Rim %Z Sponsor(s):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 Society Technical & Conference Activities Board %< avec comité de lecture %( 2015 11th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) %B 2015 11th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) %C Bangkok, Thailand %Y Dipanda, A %Y Yetongnon, K %I IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA %3 2015 11th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) %P 436-443 %8 2015-11-23 %D 2015 %R 10.1109/SITIS.2015.82 %K Twitter network %K Influence %K Information fusion %K Belief theory %Z Computer Science [cs] %Z Engineering Sciences [physics] %Z Engineering Sciences [physics]/ElectronicsConference papers %X 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. %G English %L hal-01436493 %U https://u-bourgogne.hal.science/hal-01436493 %~ UNIV-BOURGOGNE %~ CNRS %~ ENSAM %~ LE2I %~ AGREENIUM %~ LIB_UB %~ LIB-SCDONN %~ LIB-COMBINRES %~ ARTS-ET-METIERS-SCIENCES-ET-TECHNOLOGIES %~ HESAM %~ HESAM-ENSAM %~ INSTITUT-AGRO