Skip to main content

Where Are You Settling Down: Geo-locating Twitter Users Based on Tweets and Social Networks

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7675))

Abstract

In this paper, we investigate the advantages of taking two dimensions of tweet content and social relationships to construct models for predicting where people settle down as their profiles reveal city- and town-level data. Based on the users who voluntarily reveal their locations in their profiles, we propose two local word filters - Inverse Location Frequency (ILF) and Remote Words (RW) filter - to identify local words in tweets content. We also extract separately the place name mentioned in tweets using the Named Entity Recognition application and then filter them by computing the city distance. We consider users’ friends and 2-hop of followings. In our experiment, we finally combine these two dimensions to estimate user location and achieve an Accuracy of 56.6% within 100 miles in city-level and 45.2% within 25 miles in town-level of their actual location which outperforms the single dimension prediction and the baseline.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Cheng, Z., Caverlee, J., Lee, K.: You Are Where You Tweet: A Content-Based Approach to Geo-locating Twitter Users. In: 19th ACM Conference on Information and Knowledge Management, pp. 759–768. ACM, New York (2010)

    Google Scholar 

  2. Kwak, H., Lee, C., Park, H., Moon, S.: What is Twitter, a Social Network or a News Media? In: 19th International Cnference on World Wide Web, pp. 591–600. ACM, New York (2010)

    Chapter  Google Scholar 

  3. Backstrom, L., Sun, E., Marlow, C.: Find me if you can: improving geographical prediction with social and spatial proximity. In: 19th International Conference on World Wide Web, pp. 61–70. ACM, New York (2010)

    Chapter  Google Scholar 

  4. Amitay, E., Har’El, N., Sivan, R., Soffer, A.: Web-a-Where: Geotagging Web Content. In: 27th annual International ACM SIGIR Conferenceon Research and Development in Information Retrieval, pp. 273–280. ACM, New York (2004)

    Google Scholar 

  5. Kinsella, S., Murdock, V., O’Hare, N.: I’m Eating a Sandwich in Glasgow: Modeling Locations with Tweets. In: 3rd International Workshop on Search and Mining User-Generated Contents, pp. 61–68. ACM, New York (2011)

    Google Scholar 

  6. Hecht, B., Hong, L., Suh, B., Chi, B.E.: Tweets from Justin Bieber’s Heart: The Dynamics of the “Location” Field in User Profiles. In: 2011 Annual Conference on Human Factors in Computing Systems, pp. 237–246. ACM, New York (2011)

    Google Scholar 

  7. Scellato, S., Noulas, A., Mascolo, C.: Exploiting Place Features in Link Prediction on Location-based Social Networks. In: 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1046–1054. ACM, New York (2011)

    Google Scholar 

  8. Ye, M., Shou, D., Lee, W., Yin, P., Janowicz, K.: On the Semantic Annotation of Places in Location-Based Social Networks. In: 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 520–528. ACM, New York (2011)

    Google Scholar 

  9. Lin, J., Xiang, G., Hong, J.I., Sadeh, N.: Modeling People’s Place Naming Preferences in Location Sharing. In: 12th ACM International Conference on Ubiquitous Computing, pp. 75–84. ACM, New York (2010)

    Google Scholar 

  10. Fink, C., Piatko, C., Mayfield, J., Chou, D., Finin, T., Martineau, J.: The Geolocation of WebLogs from Textual Clues. In: IEEE International Conference on Computational Science and Engineering, pp. 1088–1092. IEEE Press (2009)

    Google Scholar 

  11. Li, W., Serdyukov, P., Vries, A.P., Eickhoff, C., Larson, M.: The Where in the Tweet. In: 20th ACM International Conference on Information and Knowledge Management, pp. 2473–2476. ACM, New York (2011)

    Google Scholar 

  12. Yardi, S., Boyd, D.: Tweeting from the Town Square: Measuring Geographic Local Networks. In: 4th International AAAI Conference on Weblogs and Social Media, pp. 194–201. AAAI, California (2010)

    Google Scholar 

  13. Serdyukov, P., Murdock, V., Zwol, R.: Placing Flickr Photos on a Map. In: 32nd International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 484–491. ACM, New York (2009)

    Google Scholar 

  14. Crandall, D., Backstrom, L., Huttenlocher, D., Kleinberg, J.: Mapping the World’s Photos. In: 18th International Conference on World Wide Web, pp. 761–770. ACM, New York (2009)

    Chapter  Google Scholar 

  15. Hays, J., Efros, A.: IM2GPS: estimating geographic information from a single image. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 1–8. IEEE Press (2008)

    Google Scholar 

  16. Popescu, A., Grefenstette, G.: Mining User Home Location and Gender from Flickr Tags. In: 4th International Conference on Weblogs and Social Media, pp. 307–310. AAAI, California (2010)

    Google Scholar 

  17. Gallagher, A., Joshi, D., Yu, J., Luo, J.: Geo-location Inference from Image Content and User Tags. In: IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 55–62. IEEE Press (2009)

    Google Scholar 

  18. Lee, R., Sumiya, K.: Measuring geographical regularities of crowd behaviors for Twitter-based geo-social event detection. In: 2nd ACM SIGSPATIAL International Workshop on Location Based Social Networks, pp. 1–10. ACM, New York (2010)

    Chapter  Google Scholar 

  19. Vieweg, S., Hughes, A.L., Starbird, K., Palen, L.: Microblogging during two natural hazards events: what twitter contribute to situational awareness. In: 28th International Conference on Human Factors in Computing Systems, may 2010, pp. 1079–1088. ACM, New York (2010)

    Google Scholar 

  20. Anastasios, N., Salvatore, S., Cecilia, M., Massimiliano, P.: An Empirical Study of Geographic User Activity Patterns in Foursquare. In: ICWSM 2011: 4th International Conference on Weblogs and Social Media, pp. 570–573. AAAI, California ( (2011)

    Google Scholar 

  21. Finkel, J.R., Grenager, T., Manning, C.: Incorporating Non-local Information into Information Extraction Systems by Gibbs Sampling. In: 43nd Annual Meeting of the Association for Computational Linguistics, pp. 363–370. ACL, New York (2005)

    Google Scholar 

  22. Mok, D., Wellman, B., Basu, R.: Did distance matter before the Internet? Interpersonal contact and support in the 1970s. Social Networks 29(3), 430–461 (2007)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Ren, K., Zhang, S., Lin, H. (2012). Where Are You Settling Down: Geo-locating Twitter Users Based on Tweets and Social Networks. In: Hou, Y., Nie, JY., Sun, L., Wang, B., Zhang, P. (eds) Information Retrieval Technology. AIRS 2012. Lecture Notes in Computer Science, vol 7675. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35341-3_13

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-35341-3_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-35340-6

  • Online ISBN: 978-3-642-35341-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics