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Existing methods fall short in capturing the multi-faceted and dynamic nature of developers\u2019 skills and knowledge. To address this gap, we propose a novel approach that leverages graph neural networks (GNNs) to express developers\u2019 technical expertise. Our method constructs a comprehensive GitHub social network that integrates various social and development activities. We then employ a GNN model to learn a low-dimensional representation vector for each developer, encapsulating their technical expertise across different dimensions. We assess the effectiveness of our model by comparing it against five baselines on three GitHub social relationship recommendation tasks, including SimDeveloper, ContributionRepo, and RepoMaintainer. Our proposed method outperforms these baselines, achieving improvements of 5.6\u20139.5% on Hit Ratio@10 and 3.4\u201311.1% on F1 score. These results demonstrate promising performance in predicting technical preferences for both repositories and developers. This research contributes to a more nuanced understanding of developer expertise in open-source communities and has potential implications for improving collaboration and project management on platforms like GitHub.<\/jats:p>","DOI":"10.1145\/3746451","type":"journal-article","created":{"date-parts":[[2025,6,30]],"date-time":"2025-06-30T10:19:07Z","timestamp":1751278747000},"page":"1-33","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Automatically Deriving Developers\u2019 Technical Expertise from the GitHub Social Network"],"prefix":"10.1145","volume":"35","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4756-6445","authenticated-orcid":false,"given":"Yanchun","family":"Sun","sequence":"first","affiliation":[{"name":"Key Laboratory of High Confidence Software Technologies, Ministry of Education, Beijing, China and School of Computer Science, Peking University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-5778-3795","authenticated-orcid":false,"given":"Jiawei","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Computer Science, Peking University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-7718-7453","authenticated-orcid":false,"given":"Xiaohan","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Computer Science, Peking University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-1791-743X","authenticated-orcid":false,"given":"Haizhou","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Computer Science, Peking University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4776-4932","authenticated-orcid":false,"given":"Ye","family":"Zhu","sequence":"additional","affiliation":[{"name":"Centre for Cyber Resilience and Trust, Deakin University, Melbourne, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4765-1893","authenticated-orcid":false,"given":"Zhenpeng","family":"Chen","sequence":"additional","affiliation":[{"name":"Nanyang Technological University, Singapore, Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-5332-4215","authenticated-orcid":false,"given":"Sihan","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computer Science, Peking University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-4935-7099","authenticated-orcid":false,"given":"Huizhen","family":"Jiang","sequence":"additional","affiliation":[{"name":"School of Computer Science, Peking University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4686-3181","authenticated-orcid":false,"given":"Gang","family":"Huang","sequence":"additional","affiliation":[{"name":"Key Laboratory of High Confidence Software Technologies, Ministry of Education, Beijing, China and School of Computer Science, Peking University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2026,3,11]]},"reference":[{"key":"e_1_3_2_2_2","first-page":"1","volume-title":"Proceedings of the ACM on Programming Languages","volume":"3","author":"Alon Uri","year":"2018","unstructured":"Uri Alon, Meital Zilberstein, Omer Levy, and Eran Yahav. 2018. code2vec: Learning distributed representations of code. 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