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Journal Article

Citation

Jadhao A, Kumari S, Khan F, Sultan S, Khandge R. Int. J. Innov. Sci. Eng. Technol. 2016; 2(9): 685-691.

Copyright

(Copyright © 2016, IJISET)

DOI

unavailable

PMID

unavailable

Abstract

Twitter has received much thoughtfulness recently.In this paper, we present a real-time monitoring system for traffic event detection from Twitter stream analysis. An important characteristic of Twitter is its real-time nature. The system fetches tweets from Twitter by using many search criteria; processes tweets, by usinging text mining techniques and then performs the classification of tweets. To detect a target event, we devise a classifier of tweets based on features like keywords in a tweet, the number of words, and their context. Users are using Twitter to report real-life events. It focuses on detecting those events by analyzing these text stream in Twitter.The characteristics of Twitter make it a non-trivial task.The traffic detection system was employed for real-time monitoring of many areas of the road network, that allow for detection of traffic events almost in real time.

Keywords: Twitter, Traffic event detection, tweet classification, text mining, social sensing.

SafetyLit note: We believe that the inclusion of references in this case falls under fair use. Why? 1) This article was published as open access and the journal and copyright owner is acknowledged; 2) a link to full text is provided; 3) reproduction of this reference list is relevant to a commentary on what is and is not original thought and 4) the items in this reference list are part of the data upon which an investigation are based.

References

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[6] T Sakaki, M. Okazaki, and Y.Matsuo, "Tweet analysis for real-time event detection and earthquake reporting system development," IEEE Trans.Knowl. Data Eng., vol. 25, no. 4, pp. 919–931, Apr. 2013.

[7] J. Allan, Topic Detection and Tracking: Event-Based Information Organization. Norwell, MA, USA: Kluwer, 2002.

[8] K. Perera and D. Dias, "An intelligent driver guidance tool using Location based services," in Proc. IEEE ICSDM, Fuzhou, China, 2011, pp. 246–251.

[9] T. Sakaki, Y. Matsuo, T. Yanagihara, N. P. Chandrasiri, and K. Nawa, "Real-time event extraction for driving information from social sensors," In Proc. IEEE Int. Conf. CYBER, Bangkok, Thailand, 2012, pp. 221–226.

[10] V. Gupta, S. Gurpreet, and S. Lehal, "A survey of text mining techniques and applications," J. Emerging Technol. Web Intell., vol. 1, no. 1, pp. 60–76, Aug. 2009.

Keywords: Twitter-Traffic-Status


Language: en

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