Segregating Tweets Using Machine Learning


Authors : Deva Prasad, G. Hemanth Kumar, Dr. T. Sasikala

Volume/Issue : Volume 5 - 2020, Issue 3 - March

Google Scholar : https://goo.gl/DF9R4u

Scribd : https://bit.ly/2WfJI9u

The size of informal organization information is expanding rapidly. All the different types of issues and problems are communicating in online social media platforms. This project tells us how to find out different types of issues going in social media. We all know that twitter is one of the social media platforms. So, Twitter is picking up prominence these days and the vast majority are utilizing this stage to communicate their conclusions. Slant investigation on Twitter is the utilization of breaking down the supposition of twitter data passed on by the client. The examination on this issue proclamation has developed reliably. So, this project aims to collect the all twitter data which is posted by the public users with organization hashtags. By using Sentiment analysis we will find out the tweets which is a positive comment and which is a negative comment and which is neutral. Right now, plan to portray the systems embraced, the procedure and models applied, alongside a summed-up approach utilizing python. Conclusion examination expects to decide or quantify the frame of mind of the essayist regarding some subject.

Keywords : Informal Information, segregating Tweets, Evaluating data, Text analysis, Hashtag analysis.

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Paper Submission Last Date
30 - September - 2022

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