Social networks play an important role in the dissemination of information and the spread of influence. Identifying the most influential individuals spreading information or infectious diseases can assist or hinder information dissemination, product exposure, and contagious disease detection. The leader or influential members may be even more critical to product diffusion and the formation of widespread contagions. This paper proposes a new algorithm LeadersRank, which use the network structure to identify influential members, i.e. the leaders' nodes, for community detection in social networks, without a priori knowledge of k number of communities in the network.
['Sara Ahajjam', 'Mohamed El Haddad', 'Hassan Badir']
LeadersRank: Towards a new approach for community detection in social networks