International Conference on Computer and Knowledge Engineering

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Maximum diffusion of news in social media with the approach of reducing the search space

Authors :

Masoud Karian¹

1- Maziar Higher Education Institute, Mazandaran, Iran

Keywords :

influence maximization،influential nodes،centrality،closeness،eigenvector

Abstract :

Identification of nodes that spread influence is one of the important aspects of social network analysis. These nodes are used for maximizing influence in social networks. Influence maximization is basically an NP-Hard problem. This issue, with large-scale data, faces many challenges such as accuracy and efficiency. This paper offers a new approach in this area, named RSP (Reducing search space in influence maximization Problem). This algorithm selects influential nodes based on centralities and shells of social networks. The nodes in the shortest path are of great importance in the RSP algorithm. Unlike other algorithms, this algorithm does not ignore low-degree nodes. Experimental results show that the proposed algorithm works better than RNR, MCGN, LMP, and LIR on influence spread and maintains the quality of the results in every way.

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