A Community-Based Method for Identifying Influential Nodes using Network Embedding

Abstract

People's influence on their friends' personal opinions and decisions is an essential feature of social networks, which has led to many businesses using social media to convince a small number of users to increase awareness and ultimately maximize sales to the maximum number of users. This issue is typically expressed as the influence maximization problem. In this paper, we will identify the most influential nodes in the social network during two phases. In the first phase, we offer a community detection approach based on the Node2Vec method to detect the potential communities. In the second phase, larger communities are chosen as candidate communities, and then the heuristic-based measurement approach is utilized to identify influential nodes within candidate communities. Evaluations of the proposed method on two real datasets show the superiority of this method over other compared methods.