Twitter Sentiment Analysis Project

This project collects tweets from X app, preprocesses them, and performs sentiment analysis to classify tweets as positive, negative, or neutral. The project uses the Twitter API for data collection and TextBlob for sentiment analysis.

Im using x app Developer account for API access which you can sign up for free, but limited rate since it is free.

Table of Contents

• Twitter Sentiment Analysis Project
  • Table of Contents
  • Features
  • Project Structure
  • Installation
  • Steps:
  • Usage
  • License

---

Features

• Collect tweets from Twitter based on a specific query.
• Clean and preprocess text data for analysis.
• Perform sentiment analysis using TextBlob.
• Visualize sentiment distribution.

Project Structure

twitter_sentiment_analysis/
├── config/
│   └── config.py            # Configuration file for API keys
├── data/
│   ├── tweets.csv           # Raw tweet data
│   ├── cleaned_tweets.csv   # Cleaned and preprocessed tweets
│   └── sentiment_analysis.csv # Sentiment analysis results
├── notebooks/
│   └── analysis.ipynb       # Jupyter notebook for analysis
├── src/
│   ├── data_collection.py   # Collects tweets from Twitter
│   ├── preprocess.py        # Preprocesses tweet text
│   └── sentiment_analysis.py # Analyzes sentiment of tweets
├── .env                     # Environment variables for API keys (ignored in .gitignore)
├── requirements.txt         # Python dependencies
└── README.md                # Project documentation

Installation

Prerequisites

• Python 3.6 or above
• A Twitter Developer account for API access

Steps:

• Clone this repository:

git clone https://github.com/EzioDEVio/twitter_sentiment_analysis.git
cd twitter_sentiment_analysis

• Create a virtual environment and activate it:

python -m venv env
source env/bin/activate  # On Windows, use `env\Scripts\activate`

• Install the dependencies:

pip install -r requirements.txt

• Set up your environment variables by creating a .env file:

API_KEY=your_api_key
API_SECRET=your_api_secret
ACCESS_TOKEN=your_access_token
ACCESS_SECRET=your_access_secret
BEARER_TOKEN=your_bearer_token

Usage

• Data Collection To collect tweets, run:

python -m src.data_collection

This script collects tweets based on your query and saves them in data/tweets.csv.

• Preprocessing To clean the tweet data, run:

python -m src.preprocess

This step removes URLs, mentions, hashtags, and special characters, saving results to data/cleaned_tweets.csv.

• Sentiment Analysis To perform sentiment analysis on the cleaned tweets, run:

python -m src.sentiment_analysis

This will classify each tweet as positive, neutral, or negative and save the results to data/sentiment_analysis.csv.

License

This project is licensed under the MIT License.