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Web"],"published-print":{"date-parts":[[2025,5,31]]},"abstract":"<jats:p>User location discovery from social media is crucial for location-based services such as emergency awareness and event monitoring. Existing approaches generally integrate user-generated text features and social relationships but insufficiently explore location-specific features and geographically proximate relationships, leading to suboptimal accuracy. In this article, we propose a Twitter user geolocation method based on location feature enhancement to better capture the location characteristics in users\u2019 tweets and social relationships. Specifically, a user tweet representation algorithm based on location feature separation (TwLS) is designed. By leveraging words\u2019 location-aware weight matrix and pre-trained embeddings, TwLS calculates a tweet representation for each user in every location, explicitly indicating the relevance between users and various locations. Additionally, we develop the local celebrity discovery method (LocCel) to construct social networks by identifying and preserving geographically concentrated high-degree nodes while filtering noise. Thereby, LocCel enhances local relationships and strengthens location-proximate connections within the user social network. Experiments on two real-world datasets show that our method outperforms seven baselines, improving user geolocation accuracy by 3.1% \u223c 8.1% and 1.8% \u223c 8.8%, while reducing median error by 22.2% \u223c 52.8% and 19.4% \u223c 50.7%, respectively.<\/jats:p>","DOI":"10.1145\/3711909","type":"journal-article","created":{"date-parts":[[2025,1,13]],"date-time":"2025-01-13T11:34:31Z","timestamp":1736768071000},"page":"1-24","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["Twitter User Geolocation Based on Location Feature Enhancement"],"prefix":"10.1145","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5679-6843","authenticated-orcid":false,"given":"Meng","family":"Zhang","sequence":"first","affiliation":[{"name":"Henan Key Laboratory of Cyberspace Situation Awareness, Zhengzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3225-4649","authenticated-orcid":false,"given":"Xiangyang","family":"Luo","sequence":"additional","affiliation":[{"name":"Henan Key Laboratory of Cyberspace Situation Awareness, Zhengzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1262-2360","authenticated-orcid":false,"given":"Ningbo","family":"Huang","sequence":"additional","affiliation":[{"name":"Henan Key Laboratory of Cyberspace Situation Awareness, Zhengzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9585-0574","authenticated-orcid":false,"given":"Yimin","family":"Liu","sequence":"additional","affiliation":[{"name":"Henan Key Laboratory of Cyberspace Situation Awareness, Zhengzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7572-1959","authenticated-orcid":false,"given":"Shaoyong","family":"Du","sequence":"additional","affiliation":[{"name":"Henan Key Laboratory of Cyberspace Situation Awareness, Zhengzhou, China and State Key Laboratory of Information Security, Beijing, China"}]}],"member":"320","published-online":{"date-parts":[[2025,5,26]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1145\/2488388.2488392"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.1145\/1008992.1009040"},{"key":"e_1_3_2_4_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10707-019-00354-1"},{"key":"e_1_3_2_5_2","doi-asserted-by":"publisher","DOI":"10.1145\/1772690.1772698"},{"key":"e_1_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.3115\/1119394.1119403"},{"key":"e_1_3_2_7_2","doi-asserted-by":"publisher","DOI":"10.1109\/TNSE.2021.3092204"},{"key":"e_1_3_2_8_2","doi-asserted-by":"publisher","DOI":"10.1145\/1871437.1871535"},{"key":"e_1_3_2_9_2","doi-asserted-by":"publisher","DOI":"10.1145\/2414425.2414427"},{"key":"e_1_3_2_10_2","doi-asserted-by":"publisher","DOI":"10.1109\/BigData.2014.7004256"},{"key":"e_1_3_2_11_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ipm.2020.102219"},{"key":"e_1_3_2_12_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2018.8462191"},{"key":"e_1_3_2_13_2","doi-asserted-by":"publisher","DOI":"10.1002\/asi.24011"},{"key":"e_1_3_2_14_2","first-page":"1277","volume-title":"Proceedings of the Conference on Empirical Methods in Natural Language Processing","author":"Eisenstein Jacob","year":"2010","unstructured":"Jacob Eisenstein, Brendan O\u2019Connor, Noah A. 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