Community Detection in Multilayer Networks: Challenges, Opportunities and Applications
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arXiv
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866917112061100032 |
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| author | Boukabene, Randa Tayeb, Fatima Benbouzid Si |
| author_facet | Boukabene, Randa Tayeb, Fatima Benbouzid Si |
| contents | Community detection is a fascinating and rapidly evolving field, but when it comes to analyzing networks with multiple types of interactions, referred to as multilayer networks, there is still a lot of untapped potential. Despite the wide array of methods developed to identify community structures in such networks, this area remains underexplored, leaving plenty of room for innovation. A systematic review of recent advancements is essential to understand where the field stands and where it is headed. While significant strides have been made across various disciplines, many questions remain unanswered, and new opportunities are waiting to be uncovered. In this paper, we explore the different types of multilayer networks, community detection techniques, and how they are applied in real world scenarios. We also dive into the key challenges researchers face and suggest potential directions for future work, aiming to refine community detection techniques and boost their effectiveness in multilayer networks. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_23247 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Community Detection in Multilayer Networks: Challenges, Opportunities and Applications Boukabene, Randa Tayeb, Fatima Benbouzid Si Social and Information Networks Community detection is a fascinating and rapidly evolving field, but when it comes to analyzing networks with multiple types of interactions, referred to as multilayer networks, there is still a lot of untapped potential. Despite the wide array of methods developed to identify community structures in such networks, this area remains underexplored, leaving plenty of room for innovation. A systematic review of recent advancements is essential to understand where the field stands and where it is headed. While significant strides have been made across various disciplines, many questions remain unanswered, and new opportunities are waiting to be uncovered. In this paper, we explore the different types of multilayer networks, community detection techniques, and how they are applied in real world scenarios. We also dive into the key challenges researchers face and suggest potential directions for future work, aiming to refine community detection techniques and boost their effectiveness in multilayer networks. |
| title | Community Detection in Multilayer Networks: Challenges, Opportunities and Applications |
| topic | Social and Information Networks |
| url | https://arxiv.org/abs/2511.23247 |