Real Time Traffic Detection using Twitter Tweets Analysis
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International Journal of Engineering Trends and Technology (IJETT) | 
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| © 2017 by IJETT Journal | ||
| Volume-47 Number-8 |
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| Year of Publication : 2017 | ||
| Authors : Sandeep G Panchal, Prof. R. S. Apare |
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| DOI : 10.14445/22315381/IJETT-V47P275 |
Citation
Sandeep G Panchal, Prof. R. S. Apare "Real Time Traffic Detection using Twitter Tweets Analysis", International Journal of Engineering Trends and Technology (IJETT), V47(8),458-461 May 2017. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group
Abstract
The Social sites have a huge amount of information. The social sites are as Twitter, Facebook, google + and WhatsApp. The social sites used for communication purpose. Using it the user can share an idea, thoughts, emotion, feeling, suggestions, and personal events. Twitter is best because of minimum word it expresses knowledgeable information. It follows news reporter, political leader, movies stars, and businessman. Traffic is a major issue in many cities. Social media is an active site which has many followers, using the traffic related tweets try to control traffic. To implement the real-time traffic detection and analysis of the Twitter tweets coming from those areas in the city. Android application to show and suggest graphical route format of the traffic area. Using text mining technique and natural language programming. Classify traffic related tweets, apply tokenization, stop word filtering, steaming and steam filtering. And also calculate traffic relates tweets coming from which area in latitude and longitude format. The system is real-time because the user travels from one place to another place finding a route on graphical user interface map and select route. If the system detects traffic in the route then show the traffic and suggest another alternate route for reach the destination.
References
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Keywords
NLP, Text Mining, Traffic, Twitter and Tweets.