“…Furthermore, as all the previous works used heuristic or approximation algorithm for finding the optimal solution, it is a trivial fact that the obtained solution in this research is better than the other research. Inspiring from [8,14,26,65], the alternative heuristic algorithms for finding the most influential nodes are the Greedy Degree Based (GDB); a simple heuristic that selects the k nodes with the largest degrees [3], Greedy Eigenvector Based (GEB); a simple heuristic that selects the k nodes with the largest eigenvector. GEB is suggested as a heuristic algorithm in [66], Greedy Betweenness Based (GBB); a simple heuristic that selects the k nodes with the largest Betweenness, Greedy Closeness Based (GCB); a simple heuristic that selects the k nodes with the largest Closeness, Greedy Pagerank Based (GPB); a simple heuristic that selects the k nodes with the largest Pagerank, Greedy Topsis Based (GTB); selecting the k nodes with the largest Topsis scores (this ranking method is proposed and used in [15,60,[67][68][69]), Greedy Sociability Based (GSB); Beside the existing simple method, the other simple heuristic can be selection of the k nodes with the largest social skill which is extracted by Social Skill questionnaire [61], and finally Random method (RND); simply select k random nodes in the graph.…”