Detecting Traffic from Real Time Tweets

Aswadhati Sirisha*, K. G. Prasanthi**, G. Ravikumar***
*-** Department of Master of Computer Applications, Vignan's Institute of Information Technology, Visakhapatnam, Andhra Pradesh, India.
*** Department of Information Technology, Vignan's Institute of Information Technology, Visakhapatnam, Andhra Pradesh, India.
Periodicity:October - December'2021
DOI : https://doi.org/10.26634/jse.16.2.15819

Abstract

At present, one of the major issues for a person to meet their prerequisites is the cluttered traffic. Regardless of the identity, on the off chance that are out and about to face the deal, even if an individual pursues the traffic rules. So as to determine the issue, this paper concentrates on structuring an application to dole out the genuine class mark for every single individual tweet identified with the traffic words. On the off chance that any message contains traffic related data, it will be sent as an alarm to the end clients who are following the present client, or else a similar tweet will be simply posted on the client divider. In advanced times, informal organizations have turned into an intriguing space for each human being to share and convey their ongoing updates with one another. So as to actualize this application, it picks a good online life, which is Twitter.

Keywords

Tweet Classification, Social Networks, Text Mining Technique, Twitter Stream Analysis.

How to Cite this Article?

Sirisha, A., Prasanthi, K. G., and Ravikumar, G. (2021). Detecting Traffic from Real Time Tweets. i-manager’s Journal on Software Engineering, 16(2), 1-8. https://doi.org/10.26634/jse.16.2.15819

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