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Article type: Research Article
Authors: Duan, Xiuliang | Qiu, Liqing* | Sun, Chengai
Affiliations: College of Computer Science and Engineering, Shandong University of Science and Technology, Shandong, China
Correspondence: [*] Corresponding author: Liqing Qiu, College of Computer Science and Engineering, Shandong University of Science and Technology, Shandong, China. E-mail: [email protected].
Abstract: This paper focuses on the influence maximization problem in social networks, which aims to find some influence nodes that maximize the spread of information. Most existing achievements usually adopt a uniform propagation probability, without considering the topic information. Moreover, the classic Independent Cascade Model and its approximations have suffered from much running time. To overcome this limitation, this paper proposed a Topic based Shortest Path Set algorithm (TSPS). Additionally, a comprehensive set of experiments are conducted on large real-world networks, showing that our proposal provides more impressive results in the aspects of influence spread and running time.
Keywords: Influence maximization, social networks, topic-based, heuristic algorithm
DOI: 10.3233/IDA-215790
Journal: Intelligent Data Analysis, vol. 26, no. 2, pp. 469-480, 2022
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