Sentiment Analysis Arabic.

Content

The dataset we use in our project collected in April 2019. It contains 58K Arabic tweets (47K training, 11K test) tweets annotated in positive and negative labels. The dataset is balanced and collected using positive and negative emojis lexicon.

Tech/Framework used

• Backend: Flask
• Frontend: Flutter
• ML: Tensorflow
• Related Products: Sentiment Analysis (Machine Learning)

Installation

Windows

1. Downloading the project.
2. Open folder sentiment-analysis-arabic-flask.
3. Installing requirements.txt: pip install -r requirements.txt.
4. Run server: python app.py.
5. Go to Flutter project and run main.dart.
6. Enjoy 😄

References:

• Flask tutorial: https://www.youtube.com/watch?v=MwZwr5Tvyxo&list=PL-osiE80TeTs4UjLw5MM6OjgkjFeUxCYH
• Tensorflow: https://www.tensorflow.org/
• Sentiment Analysis Arabic Model: https://github.com/motazsaad/arabic-sentiment-analysis

This project is a starting point for a Flutter application.

A few resources to get you started if this is your first Flutter project:

• Lab: Write your first Flutter app
• Cookbook: Useful Flutter samples

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