A new influential approach based on meta-huristic algorithm to identify influential users in complex social networks with the aim of increasing accuracy

Today, social networks have become more popular than in the past because they create very cheap communication channels for social communication between users. The problem of identifying influential users is to identify a set of users who, based on a specific distribution model, have a wider influence in large-scale social networks. Approaches based on topological structure analysis such as centrality criteria for identifying influential users have low accuracy and are not the optimal solution for a large social network at the same time. Therefore, a new approach that can be used in large social networks is needed. The proposed approach to identify infiltrators in social networks uses particle swarm metacognitive algorithm. The new meta-analysis approach increases the accuracy in identifying influential or influential people. In the proposed method, on average, the value of influence and distribution of the package for the Facebook dataset has been improved by 0.18 and 0.23, respectively.

A new influential approach based on meta-huristic algorithm to identify influential users in complex social networks with the aim of increasing accuracy Keywords:

Social networks , influential people , meta-analysis algorithm , influence model