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However, the lack of user adoption of geo-based features per user or per post signals that the promise of microblog services as location-based sensing systems may have only limited reach and impact. Thus, in this article, we propose and evaluate a probabilistic framework for estimating a microblog user's location based purely on the content of the user's posts. Our framework can overcome the sparsity of geo-enabled features in these services and bring augmented scope and breadth to emerging location-based personalized information services. Three of the key features of the proposed approach are: (i) its reliance purely on publicly available content; (ii) a classification component for automatically identifying words in posts with a strong local geo-scope; and (iii) a lattice-based neighborhood smoothing model for refining a user's location estimate. On average we find that the location estimates converge quickly, placing 51% of users within 100 miles of their actual location.<\/jats:p>","DOI":"10.1145\/2414425.2414427","type":"journal-article","created":{"date-parts":[[2013,2,5]],"date-time":"2013-02-05T13:19:41Z","timestamp":1360070381000},"page":"1-27","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":25,"title":["A content-driven framework for geolocating microblog users"],"prefix":"10.1145","volume":"4","author":[{"given":"Zhiyuan","family":"Cheng","sequence":"first","affiliation":[{"name":"Texas A&amp;M University, College Station, TX"}]},{"given":"James","family":"Caverlee","sequence":"additional","affiliation":[{"name":"Texas A&amp;M University, College Station, TX"}]},{"given":"Kyumin","family":"Lee","sequence":"additional","affiliation":[{"name":"Texas A&amp;M University, College Station, TX"}]}],"member":"320","published-online":{"date-parts":[[2013,2]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/1008992.1009040"},{"key":"e_1_2_1_2_1","unstructured":"Atkinson K. 2007. 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