/Twitter-Sentiment-Analysis

A TF-IDF model to predict the polarity of tweets (positive, negative, neutral)

Primary LanguageJupyter Notebook

Twitter-Sentiment-Analysis

Twitter Sentiment Analysis using the TF-IDF approach:

1- Data visualization and preprocessing
2- Data cleaning
3- Data analysis
4- TF-IDF representation
5- Train a Logistic Regression model
6- Tune model hyperparameters with Bayesian search
7- Model evaluation

Python code

The Python Jupyter Notebook to read and visualize the data and the code is available on nbviewer.