Sentiment Analysis using Logistic Regression

This repository contains the ipynb file for a machine learning model used to predict the sentiment analysis of a tweet on the popular website 'X'(formerly Twitter). It uses Logistic Regression to create a model to analyse he tweet. The dataset used has been pulled using an API request from Kaggle. This project has been made on Google Colab.

Libraries used

1. Pandas
2. Numpy
3. Sklearn:
   1. feature_extraction
   2. model_selection
   3. linearmodel
   4. metrics
4. nltk:
   1. nltk.corpus
   2. nltk.stem.porter

Results

The accuracy score of the model is about 77%. This means for every 100 entries, the model will accurately predict 77 of them.