Dynamic Traffic Analyzer Using Twitter

Harshita Rajwani, Srushti Somvanshi, Anuja Upadhye, Rutuja Vaidya, Trupti Dange

Abstract: Traffic congestion is a huge problem the world is facing nowadays. People suffer immensely in terms of money and time. In this paper, we present a system to dynamically analyze traffic and its causes, using twitter stream analysis. Twitter is a social networking site which allows people to share and read tweets. The system fetches the tweets from twitter, applies natural language processing technique on them, categorizes the tweets related to traffic, notifies the registered users about it. Natural language processing (NLP) focuses on developing efficient algorithms to process text and convert it into machine understandable language. Here, we apply NLP on the tweets to detect the traffic.

Keywords: Traffic event detection, Twitter, text mining, NLP

How to Cite?: Harshita Rajwani, Srushti Somvanshi, Anuja Upadhye, Rutuja Vaidya, Trupti Dange, "Dynamic Traffic Analyzer Using Twitter", Volume 4 Issue 10, October 2015, International Journal of Science and Research (IJSR), Pages: 984-987, https://www.ijsr.net/getabstract.php?paperid=SUB158899, DOI: https://dx.doi.org/10.21275/SUB158899