Estimation of User Location and Local Topics Based on Geographical Distribution of Microblogging
Abstract
This paper proposes a method for estimating microblogging user location to determine local topics of importance based on area-specific term co-occurrence. Geotagged information on social media has not previously been sufficient to determine local topics; however, the amount of information available on social media has continued to expand due to the widespread use of smartphones. Notably, the amount of information generated from regional cities is significantly smaller than that from metropolitan cities. Hence, we must estimate the location of each user in a regional city to obtain adequate local information for determining local topics. To extract this information, we define area-specific scores of terms and co-occurrences that are calculated using term frequency, as well as the average and standard deviation of the longitude and latitude of raw geotagged information.
References
Ishida, K. and Ohta T., “An approach for organizing knowledge according to terminology and representing it visually,” IEEE Transactions on Systems, Man, and Cybernetics, Part C, Vol. 32, No. 4, 2002, pp. 366-373.
Ishida, K., “Extracting Latent Weblog Communities: A Partitioning Algorithm for Bipartite Graphs,” Proceedings of the 2nd Annual Workshop on the Weblogging Ecosystem - Aggregation, Analysis and Dynamics in the 14th International World Wide Web Conference (WWW2005), Makuhari Messe, Chiba, Japan, May 10 - 14, 2005.
Ishida, K, "Extracting Spam Blogs with Co-citation Clusters," Proc. Of the 17th International World Wide Web Conference (WWW2008), April 21 - 25, 2008.
Dalvi N., Kumar R., and Pang B., "Object Matching in Tweets with Spatial Models," WSDM’12, Seattle, Washington, USA, February 8-12, 2012.
Bo H., Cook P., and Baldwin T., "Geolocation Prediction in Social Media Data by Finding Location Indicative Words," Proceedings of COLING 2012: Technical Papers, pp.1045-1062, COLING 2012, Mumbai, December 2012
Cheng Z., Caverlee J., and Lee K., "A Content-Driven Framework for Geolocating Microblog Users," ACM Transactions on Intelligent Systems and Technology, Vol. 4, No. 1, Article 2, Publication date: January 2013.
Backstrom, L., Kleinberg, J., Kumar, R., and Novak, J. “Spatial variation in search engine queries,” Proceeding of the 17th international conference on World Wide Web, WWW ’08, pages 357-366, Beijing, China, , April 21 - 25, 2008.
Ishida K., "Extracting Geo-Social Information based on Geo-Tagged Social Media," 4th World Congress on Social Simulation (WCSS 2012), National Chengchi University, Taipei, Taiwan, September 4-7, 2012 .
Roller S., Speriosu M., Rallapalli S., and Wing R., Jason Baldridge, "Supervised Text-based Geolocation Using Language Models on an Adaptive Grid," Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, Jeju Island, Korea, 12-14 July 2012, pp. 1500-1510.
Chandra S., Khan L., and Muhaya F. B., "Estimating Twitter User Location Using Social Interactions - A Content Based Approach," 2011 IEEE International Conference on Privacy, Security, Risk, and Trust, and IEEE International Conference on Social Computing, Boston, MA, October 9-11, 2011.
Hong L., Ahmed A., Gurumurthy S., Smola A., and Tsioutsiouliklis K., "Discovering Geographical Topics In The Twitter Stream," WWW 2012, Lyon, France, April 16-20, 2012.
