A hybrid method for community detection based on user interactions, topology and frequent pattern mining
| Title: | A hybrid method for community detection based on user interactions, topology and frequent pattern mining |
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| Authors: | Somaye Sayari, Ali Harounabadi, Touraj Banirostam |
| Source: | مجله مدل سازی در مهندسی, Vol 21, Iss 75 (2023) |
| Publisher Information: | Semnan University, 2023. |
| Publication Year: | 2023 |
| Collection: | LCC:Engineering design |
| Subject Terms: | user interactions, community detection, frequent pattern mining, local clustering coefficient, social networks, Engineering design, TA174 |
| More Details: | In recent years, community detection in social networks has become one of the most important research areas. One of the ways to community detection is to use interactions between users. There are different types of interactions in social networks, which, if used together with network topology, improve the precision of community identification. In this paper, a new method based on the combination of user interactions and network topology is proposed to community detection. In the community formation stage, the effective nodes are identified based on eigenvector centrality, and the primary communities around these nodes are formed based on frequent pattern mining. In the community expansion phase, small communities expand using modularity and the degree of interactions among users. To calculate the degree of interaction between users, a new measure based on the local clustering coefficient and interactions between common neighbors is proposed, which improves the accuracy of the degree of user interactions. Analysis of Higgs Twitter and Flickr datasets utilizing internal density metric, NMI and Omega demonstrates that the proposed method outperforms the other five community detection methods. |
| Document Type: | article |
| File Description: | electronic resource |
| Language: | Persian |
| ISSN: | 2008-4854 2783-2538 |
| Relation: | https://modelling.semnan.ac.ir/article_7850_d41d8cd98f00b204e9800998ecf8427e.pdf; https://doaj.org/toc/2008-4854; https://doaj.org/toc/2783-2538 |
| DOI: | 10.22075/jme.2023.29816.2402 |
| Access URL: | https://doaj.org/article/a7db54e8b2004790904b5f401bcbcb4f |
| Accession Number: | edsdoj.7db54e8b2004790904b5f401bcbcb4f |
| Database: | Directory of Open Access Journals |
| ISSN: | 20084854 27832538 |
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| DOI: | 10.22075/jme.2023.29816.2402 |
| Published in: | مجله مدل سازی در مهندسی |
| Language: | Persian |