Twitter-Sentiment-Analysis

This repository contains a Jupyter Notebook for performing sentiment analysis on Twitter data. The project applies natural language processing (NLP) techniques to classify tweets as positive, negative, or neutral, providing valuable insights into public opinion on various topics.

Features

• Data Preprocessing: Cleans and prepares raw Twitter data for analysis.
• Feature Extraction: Uses techniques such as TF-IDF and word embeddings.
• Model Training: Implements machine learning models (e.g., logistic regression, Naïve Bayes, or deep learning) for sentiment classification.
• Evaluation: Assesses model performance using appropriate metrics like accuracy, precision, recall, and F1-score.

Requirements

Ensure you have the necessary dependencies installed before running the notebook:

pip install pandas numpy matplotlib seaborn scikit-learn nltk