Towards Leader Based Recommendations

International audienceThe development of Internet and the success of Web 2.0 applications engendered the emergence of virtual communities. Analyzing information flows and discovering leaders through these communities becomes thus, a major challenge in different application areas. In this work, we present an algorithm that aims at detecting leaders through the use of implicit relationships with other users in behavioral networks in the context of recommender systems. This algorithm considers the high connectivity and the potentiality of propagating accurate appreciations so as to detect reliable leaders through these networks. This approach is evaluated in terms of precision using a real usage dataset. The results of the experimen- tation show the interest of our approach to exploit TopN leaders appreciations so as to generate accurate predictions through a behavioral network. Besides, our approach can be harnessed in different application areas caring about the role of leaders