Open Access Journal

ISSN : 2394-2320 (Online)

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

Open Access Journal

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

ISSN : 2394-2320 (Online)

Call For Paper : Vol 11, Issue 08, August 2024

Call for Paper

Vol 11, Issue 08, August 2024

Indexing

Analyzing tweets for Real-Time Event Detection and Development of Earthquake Reporting System

Author : Sumanth V 1 Aman A. Saxena 2 Jeevan B 3 P. Vinay 4 [Vageesha N. J. 5

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Date of Publication :14th June 2017

Abstract: Twitter, a popular micro blogging service, has received much attention recently. An important characteristic of Twitter is its real-time nature. For example, when an earthquake occurs, people make many Twitter posts (tweets) related to the earthquake, which enables detection of earthquake occurrence promptly, simply by observing the tweets. As described in this paper, we investigate the real-time inter- action of events such as earthquakes, in Twitter, and pro- pose 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 tar- get event that can find the center and the trajectory of the event location. We consider each Twitter user as a sensor and apply Kalman filtering and particle filtering, which are widely used for location estimation in ubiquitous/pervasive computing. The particle filter works better than other com- pared methods in estimating the centers of earthquakes and the trajectories of typhoons. As an application, we construct an earthquake reporting system in Japan. Because of the numerous earthquakes and the large number of Twitter users throughout the country, we can detect an earth- quake by monitoring tweets with high probability (96% of earthquakes of Japan Meteorological Agency (JMA) seismic intensity scale 3 or more are detected). Our system detects earthquakes promptly and sends e-mails to registered users. Notification is delivered much faster than the announcements that are broadcast by the JMA.

Reference :

    1. S. Arulampalam, S. Maskell, N. Gordon, and T. Clapp. A tutorial on particle filters for on-line nonlinear/non-gaussian bayesian tracking. IEEE Transactions on Signal Processing, 2001.
    2. L. Backstrom, J. Kleinberg, R. Kumar, and J. Novak. Spatial variation in search engine queries. In Proc. WWW2008, 2008.
    3. T. Bleier and F. Freund. Earthquake warning system. Spectrum, IEEE, 2005.
    4. K. Borau, C. Ullrich, J. Feng, and R. Shen. Microblogging for language learning: Using twitter to train communicative and cultural competence. In Proc. ICWL 2009, pages 78–87, 2009.
    5. d. boyd, S. Golder, and G. Lotan. Tweet, tweet, retweet: Conversational aspects of retweeting on twitter. In Proc. HICSS-43, 2010.
    6. M. Ebner and M. Schiefner. In microblogging.more than fun? In Proc. IADIS Mobile Learning Conference, 2008.
    7. D. Fox, J. Hightower, L. Liao, D. Schulz, and G. Borriello. Bayesian filters for location estimation. IEEE Pervasive Computing, 2003.
    8. G. Grosseck and C. Holotescu. Analysis indicators for communities on microblogging platforms. In Proc. eLSE Conference, 2009.
    9. J. Hightower and G. Borriello. Location systems for ubiquitous computing. IEEE Computer, 34(8):57–66, August 2001.
    10. J. Hightower and G. Borriello. Particle filters for location estimation in ubiquitous computing: A case study. In Proc. UbiComp04, 2004.
    11. B. Huberman and D. R. F. Wu. Social networks that matter: Twitter under the microscope. First Monday, 14, 2009.
    12. B. Jansen, M. Zhang, K. Sobel, and A. Chowdury. Twitter power:tweets as electronic word of mouth. Journal of the American Society for Information Science and Technology, 2009.
    13. A. Java, X. Song, T. Finin, and B. Tseng. Why we twitter: Understanding microblogging usage and communities. In Proc. Joint 9th WEBKDD and 1st SNAKDD Workshop 2007, 2007
    14. T. Joachims. Text categorization with support vector machines. In Proc. ECML’98, pages 137–142, 1998.
    15. J. Leskovec, L. Adamic, and B. Huberman. The dynamics of viral marketing. In Proc. ACM Conference on Electronic Commerce, 2006.
    16. Q. Mei, C. Liu, H. Su, and C. Zhai. A probabilistic approach to spatiotemporal theme pattern mining on weblogs. In Proc. WWW’06, 2006.
    17. Y. Matsuo and H. Yamamoto. Community gravity: measuring bidirectional effects by trust and rating on online social networks. In Proc. WWW2009, 2009.
    18. S. Milstein, A. Chowdhury, G. Hochmuth, B. Lorica, and R. Magoulas. Twitter and the micromessaging revolution: Communication,connections, and immediacy.140 characters at a time. O’Reilly Media, 2008.
    19. M. Naaman, J. Boase, and C. Lai. Is it really about me? Message content in social awareness streams. In Proc. CSCW’09, 2009.
    20. A. Passant, T. Hastrup, U. Bojars, and J. Breslin. Microblogging: A semantic and distributed approach. In Proc. SFSW2008, 2008.
    21. Y. Raimond and S. Abdallah. The event ontology, 2007. http://motools.sf.net/event/event.html.
    22. T. Rattenbury, N. Good, and M. Naaman. Towards automatic extraction of event and place semantics from flickr tags. In Proc. SIGIR 2007, 2007.
    23. E. Scordilis, C. Papazachos, G. Karakaisis, and V. Karakostas. Accelerating sesmic crustal deformation before strong mainshocks in adriatic and its importance for earthquake prediction. Journal of Seismology, 8, 2004.
    24. P. Serdyukov, V. Murdock, and R. van Zwol. Placing flickr photos on a map. In Proc. SIGIR 2009, 2009.
    25. M. Weiser. The computer for the twenty-first century. Scientific American, 268(3):94–104, 1991.

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