Inferring twitter user locations with 10km accuracy

WWW 2014 Companion - Proceedings of the 23rd International Conference on World Wide Web

Volumn , Issue , 2014, Pages 643-648

  Ryoo, KyoungMin ^a   Moon, Sue ^a  

^a Korea Advanced Institute of Science and Technology (KAIST)   (South Korea)

Author keywords

Location estimation; Microblog; Text mining

Indexed keywords

DATA MINING; FILTRATION; LOCATION; WORLD WIDE WEB;

GENERATIVE MODEL; GEOGRAPHIC LOCATION; LOCATION ESTIMATION; MICRO-BLOG; ONLINE SOCIAL NETWORKINGS; SOCIAL MEDIA PLATFORMS; TEXT MINING; TEXTUAL CONTENT;

SOCIAL NETWORKING (ONLINE);

EID: 84921716916     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2567948.2579236     Document Type: Conference Paper

References (13)

1. L. Backstrom, J. Kleinberg, R. Kumar, and J. Novak. Spatial Variation in Search Engine Queries. In Proceedings of the 17th International Conference on World Wide Web, pages 357{366. ACM, 2008.
2. L. Backstrom, E. Sun, and C. Marlow. Find Me If You Can: Improving Geographical Prediction with Social and Spatial Proximity. In Proceedings of the 19th International Conference on World Wide Web, pages 61{70. ACM, 2010.
3. Z. Cheng, J. Caverlee, and K. Lee. You Are Where You Tweet: A Content-Based Approach to Geo-Locating Twitter Users. In Proceedings of the 19th ACM International Conference on Information and Knowledge Management, pages 759{768. ACM, 2010.
4. J. Ding, L. Gravano, and N. Shivakumar. Computing Geographical Scopes of Web Resources. 2000.
5. M. R. Frank, L. Mitchell, P. S. Dodds, and C. M. Danforth. Happiness and the Patterns of Life: A Study of Geolocated Tweets. Scientific reports, 3, 2013.
6. S. goo Lee. KKMA : A Tool for Utilizing Sejong Corpus Based on Relational Database. Journal of KIISE : Computing Practices and Letters, 16(11):1046{1050, 2010.
7. B. Hecht, L. Hong, B. Suh, and E. H. Chi. Tweets from Justin Bieber's Heart: The Dynamics of the Location Field in User Profiles. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pages 237{246. ACM, 2011.
8. D. Jurgens. That's What Friends Are for: Inferring Location in Online Social Media platforms Based on Social Relationships. In Seventh International AAAI Conference on Weblogs and Social Media, 2013.
9. K. Lee, J. Caverlee, and S. Webb. Uncovering Social Spammers: Social Honeypots+ Machine Learning. In Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval, pages 435{442. ACM, 2010.
10. A. K. F. Melanie, A. Rapino. Mega Commuters in the U.S. In Association for Public Policy Analysis and Management Conference, 2013.
11. T. Pontes, M. Vasconcelos, J. Almeida, P. Kumaraguru, and V. Almeida. We Know Where You Live: Privacy Characterization of Foursquare Behavior. In Proceedings of the 2012 ACM Conference on Ubiquitous Computing, pages 898{905. ACM, 2012.
12. A. Sadilek, H. Kautz, and J. P. Bigham. Finding Your Friends and Following Them to Where You Are. In Proceedings of the Fifth ACM International Conference on Web Search and Data Mining, pages 723{732. ACM, 2012.
13. L. Wang, C. Wang, X. Xie, J. Forman, Y. Lu, W.-Y. Ma, and Y. Li. Detecting Dominant Locations from Search Queries. In Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 424{431. ACM, 2005.