{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,28]],"date-time":"2026-01-28T12:47:11Z","timestamp":1769604431291,"version":"3.49.0"},"reference-count":40,"publisher":"SAGE Publications","issue":"3","license":[{"start":{"date-parts":[[2024,12,5]],"date-time":"2024-12-05T00:00:00Z","timestamp":1733356800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"DOI":"10.13039\/501100012165","name":"Key Technologies Research and Development Program","doi-asserted-by":"publisher","award":["2022YFB3102904"],"award-info":[{"award-number":["2022YFB3102904"]}],"id":[{"id":"10.13039\/501100012165","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62172435"],"award-info":[{"award-number":["62172435"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U23A20305"],"award-info":[{"award-number":["U23A20305"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Key Research and Development Project of Henan Province","award":["221111321200"],"award-info":[{"award-number":["221111321200"]}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Intelligent Data Analysis: An International Journal"],"published-print":{"date-parts":[[2025,5]]},"abstract":"<jats:p>\n                    \n                    \n                    Mining geographic location of social media users is a crucial technology for realizing the mapping of cyberspace to geographical world, which can provide strong support for wide-ranging location-based services. As a typical approach, user geolocation methods based on relationships rely on the assumption of location homophily between users and their neighbors. However, these methods only utilize the geographic influence between pair-wise relationship, resulting in undesired geolocation performance. In this paper, a social media user geolocation method based on geographically compact social subgraphs (SMUG-GCS) is proposed. Firstly, we analyze the relationship pattern among users in geographic proximity, and find a phenomenon that users who are geographically close tend to have tightly social groups. Based on this finding, a subgraph partitioning algorithm is presented which integrates structure compactness and geographical credibility to identify a set of subgraphs, whose nodes are more tightly connected and geographically proximity. Finally, user locations are inferred using the propagation of user information only based on the geographically compact subgraph. Extensive experiments are conducted on three real-world social media datasets. The results show that,\u00a0compared with 5 typical relationship-based methods, SMUG-GCS improves the geolocating accuracy while reducing storage costs, leading to a significant reduction in median error distance ranging from 26.7% to 82.9%, as well as decrease in storage requirements by up to 56.5%.\n                  <\/jats:p>","DOI":"10.1177\/1088467x241301379","type":"journal-article","created":{"date-parts":[[2025,5,7]],"date-time":"2025-05-07T05:52:05Z","timestamp":1746597125000},"page":"748-768","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Social media user geolocation based on geographically compact subgraphs"],"prefix":"10.1177","volume":"29","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5679-6843","authenticated-orcid":false,"given":"Meng","family":"Zhang","sequence":"first","affiliation":[{"name":"State Key Laboratory of Mathematical Engineering and Advanced Computing, Henan, China"},{"name":"Key Laboratory of Cyberspace Situation Awareness of Henan Province, Henan, China"}]},{"given":"Xiangyang","family":"Luo","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Mathematical Engineering and Advanced Computing, Henan, China"},{"name":"Key Laboratory of Cyberspace Situation Awareness of Henan Province, Henan, China"}]},{"given":"Ningbo","family":"Huang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Mathematical Engineering and Advanced Computing, Henan, China"}]},{"given":"Ruixiang","family":"Li","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Mathematical Engineering and Advanced Computing, Henan, China"},{"name":"Key Laboratory of Cyberspace Situation Awareness of Henan Province, Henan, China"}]}],"member":"179","published-online":{"date-parts":[[2024,12,5]]},"reference":[{"key":"e_1_3_4_2_2","doi-asserted-by":"publisher","DOI":"10.3233\/IDA-205420"},{"key":"e_1_3_4_3_2","doi-asserted-by":"publisher","DOI":"10.3233\/IDA-216185"},{"key":"e_1_3_4_4_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11280-023-01137-3"},{"key":"e_1_3_4_5_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11280-022-01129-9"},{"key":"e_1_3_4_6_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2022.11.029"},{"key":"e_1_3_4_7_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3423165","article-title":"Location privacy-preserving mechanisms in location-based services: a comprehensive survey","volume":"54","author":"Jiang H","year":"2022","unstructured":"Jiang H, Li J, Zhao P, et al. 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