Sentiment-Analysis-for-Depression-Detection

The aim of this project is to predict whether a person is depressed or not using different machine learning algorithms based on the tweets of the user.

Setup Instructions

1. Create an account with the API provider and Get the Tweepy API Key and replace < your-api-key > in the file api_keys.py.
2. Download the Final Code.ipynb file. This file can be run in Jupyter notebook or using google colab.
3. In the Data Extraction part, after extracting the required number of tweets give keyboard interrupt and 'tweets_file.txt' will be saved.
4. After executing the entire code in Final Code.ipynb, 2 pickle files "model.pkl" and "vectorizer.pkl" files can be obtained .
5. Download the static and templates folder and app.py.
6. Setup a Flask environment in an editor of your choice (such as Visual Studio code - install a virtual environment and install flask and other required packages in the virtual environment).
7. Run the flask app - app.py file.
8. The web app will run in the localhost.