Solving the influence maximization problem by using entropy and weight of edges

The Problem of Maximizing diffusion was raised to find the number of K nodes as a subset of all social network nodes. Many other social network nodes can be activated to get information by obtaining the right nodes in this set. Solving this problem optimally will improve and increase marketing and widely transfer any information on social networks. Although many studies have investigated this issue, there are a few studies on this algorithm for providing an optimal solution. Moreover, less attention has been paid to the difference between edges and their weights in society. Therefore, this study set a score appropriate to the conditions of each node according to the topological criteria and entropy, the level of communication, and the degree of neighbors around nodes. Then, K seeds with the highest influence was carefully identified according to the scores and their measurement.