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We present a statistical mechanics approach that uses a normalized Gaussian function which captures the impact of a node within its neighborhood and leads to a density-ranking of nodes by considering the distance between nodes as punishment. A hill-climbing procedure is applied to determine the density attractors and identify the unique parent (leader) of each member as well as the group leader. This organization of the nodes results in a tree-like network with multiple clusters, the community tree. The method is tested using synthetic networks generated by the LFR benchmarking algorithm for network sizes between <jats:italic>500<\/jats:italic> and <jats:italic>30,000<\/jats:italic> nodes and mixing parameter between <jats:italic>0.1<\/jats:italic> and <jats:italic>0.9<\/jats:italic>. Our results show a reasonable agreement with the LFR results for low to medium values of the mixing parameter and indicate a very mild dependence on the size of the network.<\/jats:p>","DOI":"10.1007\/s41109-019-0216-2","type":"journal-article","created":{"date-parts":[[2019,10,23]],"date-time":"2019-10-23T04:27:21Z","timestamp":1571804841000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Community detection and unveiling of hierarchy in networks: a density-based clustering approach"],"prefix":"10.1007","volume":"4","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7529-4635","authenticated-orcid":false,"given":"Zineb","family":"Felfli","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Roy","family":"George","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Khalil","family":"Shujaee","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohamed","family":"Kerwat","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,10,22]]},"reference":[{"issue":"5","key":"216_CR1","doi-asserted-by":"publisher","first-page":"369","DOI":"10.1016\/0191-2615(96)00003-3","volume":"30","author":"T Akamatsu","year":"1996","unstructured":"Akamatsu T (1996) Cyclic flows, markov process and stochastic traffic assignment. 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