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)

Mining Twitter for Road Traffic Event Detection

Author : Sujith M S 1 Rahamathulla K 2

Date of Publication :7th May 2016

Abstract: a road traffic event detection, provides information for emergency traffic control and management purposes. Twitter is rapidly emerging as a efficient tool for the contribution and spreading of information that has an immense value for increasing awareness of traffic incidents. In this paper, a system for road traffic event detection from tweet analysis is presented. The system fetches tweets from Twitter according to several search criteria, processes the tweets by applying text mining techniques and finally classifies the tweets. The aim is to assign the appropriate class label to each tweet, whether related to a traffic event or not. The class labels used are non-traffic, traffic due to congestion or crash, and traffic due to external events. A combination of multi-class Support Vector Machine (SVM) and Decision tree classification algorithm is being implemented to classify tweets that reflect road traffic conditions. This can possibly help the drivers and concerned authorities to identify the traffic conditions in specified places.

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