Research on the Social Network Search Strategy from the Viewpoint of Comprehensive Influence Maximization
Shumin Hui* and Yuefei Wang**,
*Library, Taizhou University
No.1139 Shifu Big Road, Jiaojiang District, Taizhou, Zhejiang 318000, China
**Library, Zhejiang Normal University
688 Yingbin Road, Jinhua, Zhejiang 321004, China
Considering that social network provides a channel for nodes to exchange information, resources, and interests, the fundamental task of social network search is to find the best path from the source node to the target node. The search strategy based on the shortest path principle ignores the strength and direction of the social relationship between nodes in the social network, and ignores the difference of influence between nodes, so that the search results cannot meet the needs of searchers. Considering the important role of the influence of nodes and the influence intensity between nodes in social network search, this paper proposes the path optimization principle of maximizing the comprehensive influence, and constructs a new search algorithm based on this strategy by applying the modified Dijkstra algorithm to solve the optimal path between nodes. Using the data of typical real social networks, it is verified that the path optimization algorithm based on the principle of maximizing comprehensive impact is better than the optimization algorithm based on the shortest path, and the search results are better interpretable to users. This paper had proposed a new influence maximization algorithm which has more advantages for solving social network search with high costs or benefits consideration by taking the influence intensity of nodes or between nodes into account.
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