Location type classification using tweet content

Proceedings - 2012 11th International Conference on Machine Learning and Applications, ICMLA 2012

Volumn 1, Issue , 2012, Pages 232-237

  Liu, Haibin ^a   Luo, Bo ^b   Lee, Dongwon ^a  

^a PENNSYLVANIA STATE UNIVERSITY   (United States)

^b University of Kansas   (United States)

Author keywords

classification; location detection; social media

Indexed keywords

CHECK-IN; CLASSIFICATION ACCURACY; LOCATION CONTEXTS; LOCATION DETECTION; LOCATION SHARING; PROBABILISTIC TEXT CLASSIFICATION; SOCIAL MEDIA; SOCIAL TIES; TARGETED ADVERTISING; TEMPORAL FEATURES; TYPE CLASSIFICATIONS; USER HISTORY; USER PROFILING;

CLASSIFICATION (OF INFORMATION);

LEARNING SYSTEMS;

EID: 84873604258     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICMLA.2012.47     Document Type: Conference Paper

References (12)

1. Z. Cheng, J. Caverlee, and K. Lee, "You are where you tweet: acontent-based approach to geo-locating twitter users," in ACM CIKM,2010.
2. W. Li, P. Serdyukov, A. P. de Vries, C. Eickhoff, and M. Larson, "Thewhere in the tweet," in ACM CIKM, 2011.
3. N. Dalvi, R. Kumar, and B. Pang, "Object matching in tweets withspatial models," in ACM WSDM, 2012.
4. H.-W. Chang, D. Lee, M. Eltaher, and J. Lee, "@phillies tweetingfrom philly? predicting twitter user locations with spatial word usage,"in IEEE/ACM ASONAM, 2012.
5. Z. Cheng, J. Caverlee, K. Y. Kamath, and K. Lee, "Toward trafficdrivenlocation-based web search," in ACM CIKM, 2011.
6. M. Ye, K. Janowicz, C. Mlligann, and W.-C. Lee, "What you are iswhen you are: the temporal dimension of feature types in locationbasedsocial networks," in ACM SIGSPATIAL, 2011.
7. B. Sriram, D. Fuhry, E. Demir, H. Ferhatosmanoglu, and M. Demirbas,"Short text classification in twitter to improve informationfiltering," in ACM SIGIR, New York, NY, USA, 2010.
8. X.-H. Phan, L.-M. Nguyen, and S. Horiguchi, "Learning to classifyshort and sparse text & web with hidden topics from large-scale datacollections," in ACM WWW, 2008.
9. A. Sun, "Short text classification using very few words," in Proc. ofACM SIGIR Conference (SIGIR'12), 2012.
10. C. D. Manning, P. Raghavan, and H. Schtze, Introduction to InformationRetrieval. Cambridge University Press, 2008.
11. K. Nigam, "Using maximum entropy for text classification," in InIJCAI-99 Workshop on Machine Learning for Information Filtering,1999, pp. 61-67.
12. A. K. McCallum, "Mallet: A machine learning for language toolkit,"2002, http://mallet.cs.umass.edu.