Traffic Detection Using Tweets on Twitter Social Network

Supriya Bhosale, Sucheta Kokate

Abstract: Social networks can be employed as a source of information for event detection such as road traffic congestion and car accidents. Existing system present a real-time monitoring system for traffic event detection from twitter. The system fetches tweets from twitter and then, processes tweets using text mining techniques. Lastly performs the classification of tweets. The aim of the system is to assign the appropriate class label to each tweet, whether it is related to a traffic event or not. System employed the support vector machine as a classification model. The proposed system uses the system based on semi-supervised approach, which gives training using traffic related dataset. We propose a clustering approach for classification of the tweets in traffic related and non- traffic related tweets. We employ a Euclidean distance to calculate the similarity between the tweets.

Keywords: Tweet classification, Traffic event detection, Data mining, text mining, and social sensing

How to Cite?: Supriya Bhosale, Sucheta Kokate, "Traffic Detection Using Tweets on Twitter Social Network", Volume 4 Issue 12, December 2015, International Journal of Science and Research (IJSR), Pages: 2037-2039, https://www.ijsr.net/getabstract.php?paperid=NOV152452, DOI: https://dx.doi.org/10.21275/NOV152452