Enhancement of Gravity Centrality Measure Based on Local Clustering Method by Identifying Influential Nodes in Social Networks

Duong, Pham Van; Dinh, Xuan Truong; Sơn, Lê Hoàng; Hai, Pham Van

doi:10.1007/978-3-031-18123-8_48

Cited by 1 publication

(1 citation statement)

References 18 publications

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“…Duong et. al have investigated multiple Attributes by influence ranking of nodes [36] and VoteRank++ to find optimal influential nodes in social networks [37]. These studies have focused limited data sets with static environment of the social networks.…”

Section: Literature Reviewmentioning

confidence: 99%

A Novel Approach of Voterank-Based Knowledge Graph for Improvement of Multi-Attributes Influence Nodes on Social Networks

Pham

Duong

Tran

et al. 2023

Journal of Artificial Intelligence and Soft Computing Research

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Recently, measuring users and community influences on social media networks play significant roles in science and engineering. To address the problems, many researchers have investigated measuring users with these influences by dealing with huge data sets. However, it is hard to enhance the performances of these studies with multiple attributes together with these influences on social networks. This paper has presented a novel model for measuring users with these influences on a social network. In this model, the suggested algorithm combines Knowledge Graph and the learning techniques based on the vote rank mechanism to reflect user interaction activities on the social network. To validate the proposed method, the proposed method has been tested through homogeneous graph with the building knowledge graph based on user interactions together with influences in real-time. Experimental results of the proposed model using six open public data show that the proposed algorithm is an effectiveness in identifying influential nodes.

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Section: Literature Reviewmentioning

confidence: 99%