The Community for Technology Leaders
RSS Icon
Subscribe
Issue No.04 - April (2013 vol.25)
pp: 919-931
Takeshi Sakaki , The University of Tokyo, Tokyo
Makoto Okazaki , The University of Tokyo, Tokyo
Yutaka Matsuo , The University of Tokyo, Tokyo
ABSTRACT
Twitter has received much attention recently. An important characteristic of Twitter is its real-time nature. We investigate the real-time interaction of events such as earthquakes in Twitter and propose an algorithm to monitor tweets and to detect a target event. To detect a target event, we devise a classifier of tweets based on features such as the keywords in a tweet, the number of words, and their context. Subsequently, we produce a probabilistic spatiotemporal model for the target event that can find the center of the event location. We regard each Twitter user as a sensor and apply particle filtering, which are widely used for location estimation. The particle filter works better than other comparable methods for estimating the locations of target events. As an application, we develop an earthquake reporting system for use in Japan. Because of the numerous earthquakes and the large number of Twitter users throughout the country, we can detect an earthquake with high probability (93 percent of earthquakes of Japan Meteorological Agency (JMA) seismic intensity scale 3 or more are detected) merely by monitoring tweets. Our system detects earthquakes promptly and notification is delivered much faster than JMA broadcast announcements.
INDEX TERMS
Earthquakes, Twitter, Real time systems, Event detection, Estimation, Probabilistic logic, Blogs, earthquake, Twitter, event detection, social sensor, location estimation
CITATION
Takeshi Sakaki, Makoto Okazaki, Yutaka Matsuo, "Tweet Analysis for Real-Time Event Detection and Earthquake Reporting System Development", IEEE Transactions on Knowledge & Data Engineering, vol.25, no. 4, pp. 919-931, April 2013, doi:10.1109/TKDE.2012.29
REFERENCES
[1] M. Sarah, C. Abdur, H. Gregor, L. Ben, and M. Roger, "Twitter and the Micro-Messaging Revolution," technical report, O'Reilly Radar, 2008.
[2] A. Java, X. Song, T. Finin, and B. Tseng, "Why We Twitter: Understanding Microblogging Usage and Communities," Proc. Ninth WebKDD and First SNA-KDD Workshop Web Mining and Social Network Analysis (WebKDD/SNA-KDD '07), pp. 56-65, 2007.
[3] B. Huberman, D. Romero, and F. Wu, "Social Networks that Matter: Twitter Under the Microscope," ArXiv E-Prints, http://arxiv.org/abs0812.1045, Dec. 2008.
[4] H. Kwak, C. Lee, H. Park, and S. Moon, "What is Twitter, A Social Network or A News Media?" Proc. 19th Int'l Conf. World Wide Web (WWW '10), pp. 591-600, 2010.
[5] G.L. Danah Boyd and S. Golder, "Tweet, Tweet, Retweet: Conversational Aspects of Retweeting on Twitter," Proc. 43rd Hawaii Int'l Conf. System Sciences (HICSS-43), 2010.
[6] A. Tumasjan, T.O. Sprenger, P.G. Sandner, and I.M. Welpe, "Predicting Elections with Twitter: What 140 Characters Reveal About Political Sentiment," Proc. Fourth Int'l AAAI Conf. Weblogs and Social Media (ICWSM), 2010.
[7] P. Galagan, "Twitter as a Learning Tool. Really," ASTD Learning Circuits, p. 13, 2009.
[8] K. Borau, C. Ullrich, J. Feng, and R. Shen, "Microblogging for Language Learning: Using Twitter to Train Communicative and Cultural Competence," Proc. Eighth Int'l Conf. Advances in Web Based Learning (ICWL '09), pp. 78-87, 2009.
[9] J. Hightower and G. Borriello, "Location Systems for Ubiquitous Computing," Computer, vol. 34, no. 8, pp. 57-66, 2001.
[10] M. Weiser, "The Computer for the Twenty-First Century," Scientific Am., vol. 265, no. 3, pp. 94-104, 1991.
[11] V. Fox, J. Hightower, L. Liao, D. Schulz, and G. Borriello, "Bayesian Filtering for Location Estimation," IEEE Pervasive Computing, vol. 2, no. 3, pp. 24-33, July-Sept. 2003.
[12] T. Sakaki, M. Okazaki, and Y. Matsuo, "Earthquake Shakes Twitter Users: Real-Time Event Detection by Social Sensors," Proc. 19th Int'l Conf. World Wide Web (WWW '10), pp. 851-860, 2010.
[13] Y. Raimond and S. Abdallah, "The Event Ontology," http://motools.sf.net/eventevent.html, 2007.
[14] T. Joachims, "Text Categorization with Suport Vector Machines: Learning with Many Relevant Features," Proc. 10th European Conf. Machine Learning (ECML '98), pp. 137-142, 1998.
[15] X. Liu, S. Zhang, F. Wei, and M. Zhou, "Recognizing Named Entities in Tweets," Proc. 49th Ann. Meeting of the Assoc. for Computational Linguistics: Human Language Technologies (HLT '11), pp. 359-367, June 2011.
[16] A. Ritter, S. Clark Mausam, and O. Etzioni, "Named Entity Recognition in Tweets: An Experimental Study," Proc. Conf. Empirical Methods in Natural Language Processing, 2011.
[17] M. Arulampalam, S. Maskell, N. Gordon, and T. Clapp, "A Tutorial on Particle Filters for Online Nonlinear/Non-Gaussian Bayesian Tracking," IEEE Trans. Signal Processing, vol. 50, no. 2, pp. 174-188, Feb. 2002.
[18] J. Leskovec, L.A. Adamic, and B.A. Huberman, "The Dynamics of Viral Marketing," Proc. Seventh ACM Conf. Electronic Commerce (EC '06), pp. 228-237, 2006.
[19] Y. Matsuo and H. Yamamoto, "Community Gravity: Measuring Bidirectional Effects by Trust and Rating on Online Social Networks," Proc. 18th Int'l Conf. World Wide Web (WWW '09), pp. 751-760, 2009.
[20] W. Zhu, C. Chen, and R.B. Allen, "Analyzing the Propagation of Influence and Concept Evolution in Enterprise Social Networks Through Centrality and Latent Semantic Analysis," Proc. 12th Pacific-Asia Conf. Advances in Knowledge Discovery and Data Mining (PAKDD '08), pp. 1090-1098, 2008.
[21] E. Scordilis, C. Papazachos, G. Karakaisis, and V. Karakostas, "Accelerating Seismic Crustal Deformation before Strong Mainshocks in Adriatic and Its Importance for Earthquake Prediction," J. Seismology, vol. 8, pp. 57-70, http://dx.doi.org/10.1023B:JOSE.0000009504.69449.48 , 2004.
[22] T. Bleier and F. Freund, "Earthquake [earthquake warning systems]," IEEE Spectrum, vol. 42, no. 12, pp. 22-27, Dec. 2005.
[23] M. Cataldi, L. Di Caro, and C. Schifanella, "Emerging Topic Detection on Twitter Based on Temporal and Social Terms Evaluation," Proc. 10th Int'l Workshop Multimedia Data Mining (MDMKDD '10), pp. 1-10, 2010.
[24] B. O'Connor, R. Balasubramanyan, B.R. Routledge, and N.A. Smith, "From Tweets to Polls: Linking Text Sentiment to Public Opinion Time Series," Proc. Int'l AAAI Conf. Weblogs and Social Media, 2010.
[25] M. Ebner and M. Schiefner, "Microblogging - More than Fun?" Proc. IADIS Mobile Learning Conf., pp. 155-159, 2008.
[26] A. Passant, T. Hastrup, U. Bojars, and J. Breslin, "Microblogging: A Semantic Web and Distributed Approach," Proc. Fourth Workshop Scripting for the Semantic Web (SFSW '08), http://data. semanticweb.org/workshop/scripting/ 2008/paper11, 2008.
[27] L. Backstrom, J. Kleinberg, R. Kumar, and J. Novak, "Spatial Variation in Search Engine Queries," Proc. 17th Int'l Conf. World Wide Web (WWW '08), pp. 357-366, 2008.
[28] Q. Mei, C. Liu, H. Su, and C. Zhai, "A Probabilistic Approach to Spatiotemporal Theme Pattern Mining on Weblogs," Proc. 15th Int'l Conf. World Wide Web (WWW '06), pp. 533-542, 2006.
[29] P. Serdyukov, V. Murdock, and R. van Zwol, "Placing Flickr Photos on a Map," Proc. 32nd Int'l ACM SIGIR Conf. Research and Development in Information Retrieval (SIGIR '09), pp. 484-491, 2009.
[30] T. Rattenbury, N. Good, and M. Naaman, "Towards Automatic Extraction of Event and Place Semantics from Flickr Tags," Proc. 30th Ann. Int'l ACM SIGIR Conf. Research and Development in Information Retrieval (SIGIR '07), pp. 103-110, 2007.
[31] J. Hightower and G. Borriello, "Particle Filters for Location Estimation in Ubiquitous Computing: A Case Study," Proc. Int'l Conf. Ubiquitous Computing (UbiComp '04), pp. 88-106, 2004.
6 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool