… Identifying social influence in networks is critical to understanding how … influence and
susceptibility in networks while avoiding the biases inherent in traditional estimates of social …

… In this paper, we present an algorithm for community detection with focus on social networks…
on social networks and model the dynamic social interactions that occur on those networks. …

… influential communities in a meta-community. To this end, we propose a new definition of an
influential community … to identify influential communities in each meta-community. Although, …

… First, we identify influential users and communities by means of a network analysis of the …
of the communities according to the main interests and profile of their most influential users. …

… into different communities according to their common interests. We propose two algorithms
to detect influential communities using common interests in large social networks efficiently …

… type of influence-based … influential users in online social networks on the basis of a simple
metric of their activity level. In this article, we consider a user “influential” in a social network if …

… as a representative of such communities. In particular, we measure the influence that opinion
leaders have on the public and the entire virtual community in the social network service. …

… In order to quantify the influential communities we have introduced a measure known as
the normalized community overlap factor, \(N_{p,q}\). It is defined as the ratio between the …

… selects the seed nodes based on the community detection approach. So, in this section,
the new algorithm for maximizing the influence in social networks (called IMBC) is presented. …

… In the social network, we would like to detect the cohesive subgroups that consist of many
celebrities, as these subgroups act important roles for information dissemination and spread …