Proceedings of the 3rd Workshop on Noisy User-Generated Text 2017
DOI: 10.18653/v1/w17-4415
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Huntsville, hospitals, and hockey teams: Names can reveal your location

Abstract: Geolocation is the task of identifying a social media user's primary location, and in natural language processing, there is a growing literature on to what extent automated analysis of social media posts can help. However, not all content features are equally revealing of a user's location. In this paper, we evaluate nine name entity (NE) types. Using various metrics, we find that GEO-LOC, FACILITY and SPORT-TEAM are more informative for geolocation than other NE types. Using these types, we improve geolocatio… Show more

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Cited by 10 publications
(10 citation statements)
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“…Brunsting et al [4] showed an approach of geographical information tagging into textual documents. Salehi et al [5] described how a name can reveal one's location. Chi et al [6] explored the importance of location indicative words for location prediction in a tweet.…”
Section: Related Workmentioning
confidence: 99%
“…Brunsting et al [4] showed an approach of geographical information tagging into textual documents. Salehi et al [5] described how a name can reveal one's location. Chi et al [6] explored the importance of location indicative words for location prediction in a tweet.…”
Section: Related Workmentioning
confidence: 99%
“…Prior studies showed that many regionallydistributed content words are topically driven (Eisenstein et al, 2010;Salehi et al, 2017). People talk more about their own region than about others, so the most indicative words include place names (the own city, or specific places within that city), and other local culture terms, such as sports teams.…”
Section: Preprocessingmentioning
confidence: 99%
“…They used a sample of 26 million tweets in their study, obtained through the public Twitter API. Salehi et al (2017) evaluate nine name entity types. Using various metrics, they find that GEO-LOC, FACILITY and SPORT-TEAM are more informative for geolocation than other NE types.…”
Section: Related Workmentioning
confidence: 99%