Estimation of traffic with accuracy through Twitter stream analysis
Internet sites are source of info for event detection, with specific mention of the road traffic activity blockage and accidents or earth quack sensing system. In this paper, we present a real time monitoring system intended for traffic occasion detection coming from Twitter stream analysis. The system fetches tweets coming from Twitter as per a several search criteria; methods tweets, by applying textual content mining methods; last but not least works the classification of twitter posts. The goal is to assign suitable class packaging to every tweet, because related with an activity of traffic event or perhaps not. The traffic recognition system or framework was utilized for real time monitoring of various areas of the street network, taking into account detection of traffic occasions just almost in actual time, regularly before on line traffic news sites. All of us employed the support vector machine like a classification unit; furthermore, we accomplished a great accuracy value of ninety five. 75% by attempting a binary classification issue. All of us were also capable to discriminate if traffic is triggered by an external celebration or not, by resolving a multiclass classification issue and obtaining accuracy worth of 88. 89% Keywords: Traffic Event Detection, Tweet Classification, Text Mining, And Social Sensing. Available at may be viewed at: ijitech.org/uploads/543216IJIT9948 234.pdf Keywords: Twitter Traffic Status 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: [1] Eleonora D'Andrea, Pietro Ducange, Beatrice Lazzerini, Member, IEEE, and Francesco Marcelloni, Member, IEEE, "Real Time Detection of Traffic From Twitter Stream Analysis" IEEE Transactions on Intelligent Transportation Systems, Vol. 16, No. 4, August 2015. [2] F. Atefeh and W. Khreich, "A survey of techniques for event detection in Twitter," Comput. Intell. vol. 31, no. 1, pp. 132 164, 2015. [3] P. Ruchi and K. Kamalakar, "ET: Events from tweets," in Proc. 22nd Int. Conf. World Wide Web Comput. Rio de Janeiro, Brazil, 2013, pp. 613 620. [4] A. Mislove, M. Marcon, K. P. Gummadi, P. Druschel, and B. Bhattacharjee, "Measurement and analysis of online social networks," in Proc. 7th ACM SIGCOMM Conf. Internet Meas. San Diego, CA, USA, 2007, pp. 29 42. [5] G. Anastasi et al. "Urban and social sensing for sustainable mobility in smart cities," in Proc. IFIP/IEEE Int. Conf. Sustainable Internet ICT Sustainability, Palermo, Italy, 2013, pp. 1 4. [6] A. Rosi et al. "Social sensors and pervasive services: Approaches and perspectives," in Proc. IEEE Int. Conf. PERCOM Workshops, Seattle, WA, USA, 2011, pp. 525 530. [7] 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. [8] J. Allan, Topic Detection and Tracking: Event Based Information Organization. Norwell, MA, USA: Kluwer, 2002. [9] K. Perera and D. Dias, "An intelligent driver guidance tool using location based services," in Proc. IEEE ICSDM, Fuzhou, China, 2011, pp. 246 251. [10] 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. [11] B. Chen and H. H. Cheng, "A review of the applications of agent technology in traffic and transportation systems," IEEE Trans. Intell. Transp. Syst. vol. 11, no. 2, pp. 485 497, Jun. 2010. [12] A. Gonzalez, L. M. Bergasa, and J. J. Yebes, "Text detection and recognition on traffic panels from street level imagery using visual appearance," IEEE Trans. Intell. Transp. Syst. vol. 15, no. 1, pp. 228 238, Feb. 2014. Language: en