By Subhayu Roy
Tweets are not under-rated for no reason. Here, I have done a Tweet Analysis on some selected tweets, which has been categorized by Kaggle. The language I have used is Python3.8.
This is a detailed analysis of the emotional values and expressions of all the tweets, to see, whether hate prevails or love(negative or positive respectively).
For performing this analysis, the [dataset](https://raw.githubusercontent.com/kolaveridi/kaggle-Twitter-US-Airline-Sentiment-/master/Tweets.csv) is used is from [Kaggle](https://www.kaggle.com/).
For easy understanding, ***lots of appropriate visualizations*** have been used.
The language used is Python 3.8 in the Ubuntu environment.
This is an NLP project written in Python in a [Jupyter Notebook](https://jupyter.org/try).
The techniques used are:
- Word Vector
- Text Classification
- Tokenizing
- Text Processing
- Pattern Matching
The **accuracy score** of this model is *0.7599043715846995* which is equivalent to *75.99%*
Submitted by Subhayu Roy (Subhayu)
Download packets of source code on Coders Packet
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