{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/hidden-community-detection-in-social-networks","title":"Hidden Community Detection in Social Networks","arxiv_id":"1702.07462","date":"2017-02-24","proceeding":null,"authors":["Kun He","Yingru Li","Sucheta Soundarajan","John E. Hopcroft"],"abstract":"We introduce a new paradigm that is important for community detection in the\nrealm of network analysis. Networks contain a set of strong, dominant\ncommunities, which interfere with the detection of weak, natural community\nstructure. When most of the members of the weak communities also belong to\nstronger communities, they are extremely hard to be uncovered. We call the weak\ncommunities the hidden community structure.\n  We present a novel approach called HICODE (HIdden COmmunity DEtection) that\nidentifies the hidden community structure as well as the dominant community\nstructure. By weakening the strength of the dominant structure, one can uncover\nthe hidden structure beneath. Likewise, by reducing the strength of the hidden\nstructure, one can more accurately identify the dominant structure. In this\nway, HICODE tackles both tasks simultaneously.\n  Extensive experiments on real-world networks demonstrate that HICODE\noutperforms several state-of-the-art community detection methods in uncovering\nboth the dominant and the hidden structure. In the Facebook university social\nnetworks, we find multiple non-redundant sets of communities that are strongly\nassociated with residential hall, year of registration or career position of\nthe faculties or students, while the state-of-the-art algorithms mainly locate\nthe dominant ground truth category. In the Due to the difficulty of labeling\nall ground truth communities in real-world datasets, HICODE provides a\npromising approach to pinpoint the existing latent communities and uncover\ncommunities for which there is no ground truth. Finding this unknown structure\nis an extremely important community detection problem.","url_abs":"http://arxiv.org/abs/1702.07462v1","url_pdf":"http://arxiv.org/pdf/1702.07462v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"hidden-community-detection-in-social-networks","repo_url":"https://github.com/KunHe2015/HiCode","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"hidden-community-detection-in-social-networks","repo_url":"https://github.com/AbinavRavi/Network_Analysis_Eur_Parl","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"hidden-community-detection-in-social-networks","repo_url":"https://github.com/GamesResearchTUG/HiCode","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"hidden-community-detection-in-social-networks","repo_url":"https://github.com/JHL-HUST/HiCode","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"community-detection","task_name":"Community Detection"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}