kipsangmarion / nltk-twitter-sentiment-analysis

Sentiment analysis on twitter samples dataset

Twitter Sentiment Analysis using NLTK and scikit-learn

Introduction:

This Jupyter Notebook provides a step-by-step guide to performing sentiment analysis on Twitter data using Natural Language Toolkit (NLTK) and scikit-learn in Python. Sentiment analysis aims to determine the sentiment expressed in text data, which can be useful for understanding public opinion, customer feedback, and more.

Dependencies:

• Python 3.x
• Jupyter Notebook
• NLTK
• scikit-learn

Installation:

1. Make sure you have Python 3.x installed. You can download it from the official Python website.

2. Install Jupyter Notebook by running pip install jupyter in your terminal or command prompt.

3. Install NLTK by running pip install nltk.

4. Install scikit-learn by running pip install scikit-learn.

Usage:

1. Clone or download the repository containing the Jupyter Notebook.

2. Open Jupyter Notebook by running jupyter notebook in your terminal or command prompt. Navigate to the directory where the notebook is located.

3. Open the notebook (Twitter-sentiment-analysis.ipynb) by clicking on it.

4. Follow the instructions in the notebook to execute each cell sequentially. Make sure to run any cells that contain imports, function definitions, or variable assignments before running subsequent cells.

5. The notebook guides you through the process of accessing Twitter data, preprocessing the text, extracting features, training machine learning models, and evaluating their performance.

References:

• NLTK documentation: https://www.nltk.org/
• scikit-learn documentation: https://scikit-learn.org/stable/documentation.html
• Twitter Developer Platform: https://developer.twitter.com/en/docs

Feel free to reach out if you have any questions or suggestions!