This repository contains a ml model that can process tweets and can predict whether they have positive or negative sentiment attached with them
It contains 1,600,000 tweets extracted using the twitter api . The tweets have been annotated (0 = negative, 4 = positive) and they can be used to detect sentiment .
It contains the following 6 fields: 1.target: the polarity of the tweet (0 = negative, 2 = neutral, 4 = positive)
2.ids: The id of the tweet ( 2087)
3.date: the date of the tweet (Sat May 16 23:58:44 UTC 2009)
4.flag: The query (lyx). If there is no query, then this value is NO_QUERY.
5.user: the user that tweeted (robotickilldozr)
6.text: the text of the tweet (Lyx is cool)
Technologies used:Numpy,Pandas,Matplotlib,Seaborn,Scikit-Learn.