The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.
Tweet Analysis for Real-Time Event Detection and Earthquake Reporting System Development
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.
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A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking
Arulampalam, M. S., Maskell, S., Gordon, N., & Clapp, T. (2002) · IEEE Transactions on Signal Processing · doi:10.1109/78.978374 · Cited by 11,502
The Computer for the 21st Century
Weiser, M. (1991) · Scientific American · doi:10.1038/scientificamerican0991-94 · Cited by 10,017
Text categorization with Support Vector Machines: Learning with many relevant features
Joachims, T. (1998) · Lecture Notes in Computer Science · doi:10.1007/bfb0026683 · Cited by 7,999
What is Twitter, a social network or a news media?
Kwak, H., Lee, C., Park, H., & Moon, S. (2010) · Proceedings of the 19th international conference on World wide web · doi:10.1145/1772690.1772751 · Cited by 6,652
Earthquake shakes Twitter users: real-time event detection by social sensors
Sakaki, T., Okazaki, M., & Matsuo, Y. (2010) · Proceedings of the 19th international conference on World wide web · doi:10.1145/1772690.1772777 · Cited by 3,640
Self-citationLocation systems for ubiquitous computing
Hightower, J., & Borriello, G. (2001) · Computer · doi:10.1109/2.940014 · Cited by 2,987
Predicting Elections with Twitter: What 140 Characters Reveal about Political Sentiment
Tumasjan, A., Sprenger, T., Sandner, P., & Welpe, I. (2010) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v4i1.14009 · Cited by 2,649
Why we twitter: understanding microblogging usage and communities
Java, A., Song, X., Finin, T., & Tseng, B. (2007) · Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web mining and social network analysis · doi:10.1145/1348549.1348556 · Cited by 2,645
The Computer for the Twenty-First Century
Weiser, M. (1991) · Scientific American · Cited by 2,113
Tweet, Tweet, Retweet: Conversational Aspects of Retweeting on Twitter
Boyd, D., Golder, S., & Lotan, G. (2010) · 2010 43rd Hawaii International Conference on System Sciences · doi:10.1109/hicss.2010.412 · Cited by 2,051
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Open challenges for data stream mining research
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Metadata
- Authors
- Sakaki, T., Okazaki, M., & Matsuo, Y.
- Venue
- IEEE Transactions on Knowledge and Data Engineering
- Published
- 2013-04
- Volume
- 25
- Issue
- 4
- Pages
- 919-931
- ISSN
- 1041-4347 (ISSN-L)
- OpenAlex
- W2166202924
- Cited by
- 502
- References
- 26
- FWCI
- 20.26
- Type
- journal article
- Language
- en
- Open access
- closed
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