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Information Journal Paper

Title

An Improved Method for Community Detection in Dynamic Social Networks Based on Label Propagation and Modularity Optimization

Pages

  55-69

Abstract

Community Detection in Dynamic Social Networks is one of the most important research topics that has been considered in recent years. There are various approaches to detecting communities in Dynamic Social Networks, among which the Label Propagation Approach has chosen due to simplicity and efficiency. This approach involves many methods that are often random. Among these methods, LabelRankT(Time) is a deterministic method. Of course, this method also has problems, one of the problems is that when a node wants to join a community, the internal structure of that community is not considered. So, for solving this problem, a greedy approach has been used to improve the label publishing approach. The proposed approach and other evaluated methods are tested in real and Synthetic datasets. The results show that the proposed method has performed relatively better than the other methods in terms of accuracy and modularity.

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    APA: Copy

    SATTARI, MOHAMMAD, & Zamanifar, Kamran. (2020). An Improved Method for Community Detection in Dynamic Social Networks Based on Label Propagation and Modularity Optimization. IRANIAN COMMUNICATION AND INFORMATION TECHNOLOGY, 12(43-44 ), 55-69. SID. https://sid.ir/paper/370168/en

    Vancouver: Copy

    SATTARI MOHAMMAD, Zamanifar Kamran. An Improved Method for Community Detection in Dynamic Social Networks Based on Label Propagation and Modularity Optimization. IRANIAN COMMUNICATION AND INFORMATION TECHNOLOGY[Internet]. 2020;12(43-44 ):55-69. Available from: https://sid.ir/paper/370168/en

    IEEE: Copy

    MOHAMMAD SATTARI, and Kamran Zamanifar, “An Improved Method for Community Detection in Dynamic Social Networks Based on Label Propagation and Modularity Optimization,” IRANIAN COMMUNICATION AND INFORMATION TECHNOLOGY, vol. 12, no. 43-44 , pp. 55–69, 2020, [Online]. Available: https://sid.ir/paper/370168/en

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