The DOI matches its Crossref record; 102 of the 102 references it cites were found in a registry or an index.
Community detection in social networks
Abstract
The expansion of the web and emergence of a large number of social networking sites (SNS) have empowered users to easily interconnect on a shared platform. A social network can be represented by a graph consisting of a set of nodes and edges connecting these nodes. The nodes represent the individuals/entities, and the edges correspond to the interactions among them. The tendency of people with similar tastes, choices, and preferences to get associated in a social network leads to the formation of virtual clusters or communities. Detection of these communities can be beneficial for numerous applications such as finding a common research area in collaboration networks, finding a set of likeminded users for marketing and recommendations, and finding protein interaction networks in biological networks. A large number of community‐detection algorithms have been proposed and applied to several domains in the literature. This paper presents a survey of the existing algorithms and approaches for the detection of communities in social networks. We also discuss some of the applications of community detection. WIREs Data Mining Knowl Discov 2016, 6:115–135. doi: 10.1002/widm.1178 This article is categorized under: Algorithmic Development > Structure Discovery
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Cites
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Cited by
Community detection in networks: A multidisciplinary review
Javed, M. A., Younis, M. S., Latif, S., Qadir, J., & Baig, A. (2018) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2018.02.011 · Cited by 499
How to Find Orchestrated Trolls? A Case Study on Identifying Polarized Twitter Echo Chambers
Kratzke, N. (2023) · Computers · doi:10.3390/computers12030057 · Cited by 13
Metadata
- Authors
- Bedi, P., & Sharma, C.
- Venue
- WIREs Data Mining and Knowledge Discovery
- Publisher
- Wiley
- Published
- 2016-02-19
- Volume
- 6
- Issue
- 3
- Pages
- 115-135
- ISSN
- 1942-4787 (ISSN-L)
- 1942-4795
- OpenAlex
- W2290805605
- Cited by
- 346
- References
- 102
- FWCI
- 15.37
- Type
- journal article
- Language
- en
- Open access
- closed
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