Sentiment Analysis Twitter Word2vec Keras

A tweet sentiment classifier using word2vec and Keras. This Keras model can be saved and used on other tweet data, like streaming data extracted through the tweepy API.

Digital Marketing & SEOJupyter NotebookGPL-3.0

Abstract

Sentiment Analysis Twitter Word2vec Keras is an open-source Digital Marketing & SEO project. A tweet sentiment classifier using word2vec and Keras. This Keras model can be saved and used on other tweet data, like streaming data extracted through the tweepy API. A tweet sentiment classifier using word2vec and Keras. The combination of these two tools resulted in a 86% training accuracy and 73 % validation accuracy. It is built using Jupyter Notebook, NLP, Deep Learning, Keras. The complete source code is publicly available on GitHub under the GNU General Public License v3.0, making it a useful reference for students building a Digital Marketing & SEO mini project or final-year project.

1. Introduction

A tweet sentiment classifier using word2vec and Keras. The combination of these two tools resulted in a 86% training accuracy and 73 % validation accuracy. This Keras model can be saved and used on other tweet data, like streaming data extracted through the tweepy API. There is so much scope to improve the model and implement it for different purposes involving sentiment analysis of twitter data.

2. Objective

A tweet sentiment classifier using word2vec and Keras. This Keras model can be saved and used on other tweet data, like streaming data extracted through the tweepy API.

This project demonstrates how Jupyter Notebook, NLP, Deep Learning can be applied to a real-world Digital Marketing & SEO problem.

4. Technology Stack

Jupyter NotebookNLPDeep LearningKeras

5. System Requirements

General requirements for this technology stack — check the README for exact versions.

  • Python 3.8 or later with Jupyter Notebook / JupyterLab (or Google Colab)
  • pip for dependencies
  • Git (to clone the repository)

6. Installation & Setup

git clone https://github.com/akanshajainn/Sentiment-Analysis-Twitter-word2vec-keras.git
cd Sentiment-Analysis-Twitter-word2vec-keras

Full setup instructions are in the project README.

7. Future Enhancements

Suggested extensions you can add to make this your own project.

  • Export reports to Google Sheets or PDF
  • Schedule weekly automated reports
  • Add competitor comparison

8. Viva / Review Questions

Common questions examiners ask for projects in this domain.

  1. Which marketing or SEO problem does this tool solve?
  2. Which data sources or APIs does it use (Search Console, Analytics, social platforms)?
  3. Which metrics or KPIs does it report and how are they calculated?
  4. How could the output help a business make decisions?
  5. How would you schedule it to run automatically?

9. Source Code & License

This project is developed by akanshajainn and published on GitHub under the GNU General Public License v3.0. Please follow the license terms and credit the original author when you use or modify this code.

View Source on GitHubDownload ZIP

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