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The choice and evaluation of such algorithm performance is challenging because of the lack of a comprehensive set of benchmarks and specific metrics. To address these challenges, we propose CoD\u00c6N\u2014Community Detection Algorithms in Evolving Networks\u2014a benchmarking framework for evolutionary CD algorithms in dynamic networks, that we offer as open source to the community. CoD\u00c6N allows us to generate synthetic community-structured graphs with known ground truth and design evolving scenarios combining nine basic graph transformations that modify edges, nodes, and communities. We propose three complementary metrics (i.e., Correctness, Delay, and Stability) to compare evolutionary CD algorithms.\n          <\/jats:p>\n          <jats:p>Armed with CoD\u00c6N, we consider three evolutionary modularity-based CD approaches, dissecting their performance to gauge the trade-off between the stability of the communities and their correctness. Next, we compare the algorithms in real Web-oriented datasets, confirming such a trade-off. Our findings reveal that algorithms that introduce memory in the graph maximise stability but add delay when abrupt changes occur. Conversely, algorithms that introduce memory by initialising the CD algorithms with the previous solution fail to identify the split and birth of new communities. These observations underscore the value of CoD\u00c6N in facilitating the study and comparison of alternative evolutionary community detection algorithms.<\/jats:p>","DOI":"10.1145\/3718988","type":"journal-article","created":{"date-parts":[[2025,2,20]],"date-time":"2025-02-20T05:49:06Z","timestamp":1740030546000},"page":"1-25","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["CoD\u00c6N: Benchmarks and Comparison of Evolutionary Community Detection Algorithms for Dynamic Networks"],"prefix":"10.1145","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1764-7666","authenticated-orcid":false,"given":"Giordano","family":"Paoletti","sequence":"first","affiliation":[{"name":"Department of Control and Computer, Politecnico di Torino","place":["Torino, Italy"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8258-8626","authenticated-orcid":false,"given":"Luca","family":"Gioacchini","sequence":"additional","affiliation":[{"name":"Department of Electronics and Telecommunications, Politecnico di Torino","place":["Torino, Italy"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1859-6693","authenticated-orcid":false,"given":"Marco","family":"Mellia","sequence":"additional","affiliation":[{"name":"Department of Control and Computer, Politecnico di Torino","place":["Torino, Italy"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2920-1856","authenticated-orcid":false,"given":"Luca","family":"Vassio","sequence":"additional","affiliation":[{"name":"Department of Control and Computer, Politecnico di Torino","place":["Torino, Italy"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9142-2919","authenticated-orcid":false,"given":"Jussara","family":"Almeida","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Universidade Federal de Minas Gerais","place":["Belo Horizonte, Brazil"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2025,8,22]]},"reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"publisher","unstructured":"Anton Abilov and Yiqing Hua. 2021. 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