{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/semi-supervised-user-geolocation-via-graph","title":"Semi-supervised User Geolocation via Graph Convolutional Networks","arxiv_id":"1804.08049","date":"2018-04-22","proceeding":"ACL 2018 7","authors":["Afshin Rahimi","Trevor Cohn","Timothy Baldwin"],"abstract":"Social media user geolocation is vital to many applications such as event\ndetection. In this paper, we propose GCN, a multiview geolocation model based\non Graph Convolutional Networks, that uses both text and network context. We\ncompare GCN to the state-of-the-art, and to two baselines we propose, and show\nthat our model achieves or is competitive with the state- of-the-art over three\nbenchmark geolocation datasets when sufficient supervision is available. We\nalso evaluate GCN under a minimal supervision scenario, and show it outperforms\nbaselines. We find that highway network gates are essential for controlling the\namount of useful neighbourhood expansion in GCN.","url_abs":"http://arxiv.org/abs/1804.08049v4","url_pdf":"http://arxiv.org/pdf/1804.08049v4.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"semi-supervised-user-geolocation-via-graph","repo_url":"https://github.com/afshinrahimi/geographconv","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}}],"tasks":[{"task_slug":"event-detection","task_name":"Event Detection"}],"methods":[{"method_slug":"gcn","method_name":"GCN"},{"method_slug":"graph-convolutional-networks","method_name":"Graph Convolutional Networks"},{"method_slug":"highway-layer","method_name":"Highway Layer"},{"method_slug":"highway-network","method_name":"Highway Network"},{"method_slug":"sigmoid-activation","method_name":"Sigmoid Activation"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1804.08049","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1804.08049"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/afshinrahimi/geographconv","reach":{"status":"ok"}}],"summary":{"ran_honours":1},"by_repo_kind":{},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":1,"samples":[{"code_sha256_prefix":"91fe7a23c1c052b7","entry":"softmax","repo":null,"repo_kind":null,"path":null,"file_url":null,"link_basis":"identical_code_first_harvested_elsewhere","language":"python","status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":null,"inline_ok":false,"mcp_get_code":{"code_sha256":"91fe7a23c1c052b7"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}