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The backend and ML code for sentiment analysis. Evaluating words to determine sentiments and opinions that may be positive or negative in polarity.

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How to Run

Installation

Note: Make sure sentiment_analysis_ml_part and web_sentiment_analysis are in a single root directory.

Python Server

Note: Make sure you have installed Microsoft C++ Build Tools before proceeding.

  1. Install anaconda
  2. In terminal, navigate to sentiment_analysis_ml_part directory in anaconda part.
  3. Run conda env create -n sentiment_analysis -f ./environment.yml
  4. Activate the environment by running conda activate sentiment_analysis
  5. Run this command python -m spacy download en_core_web_sm
  6. Type in terminal set FLASK_APP=server.py
  7. Then run flask run

Nodejs Server

Note: Make sure you have installed Nodejs and MongoDB before proceeding

  1. Navigate to web_sentiment_analysis directory in CMD.
  2. Type the command npm install

Running The Project

Python Server

  1. Navigate to sentiment_analysis_ml_part directory in anaconda prompt.
  2. Type in terminal set FLASK_APP=server.py
  3. Then run flask run

Nodejs Server

Note: Make sure you have installed Nodejs and MongoDB before proceeding

  1. Navigate to web_sentiment_analysis directory in CMD.
  2. Type the command npm run start

The server will start. First time will take long because the models have to be trained and saved.

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The backend and ML code for sentiment analysis. Evaluating words to determine sentiments and opinions that may be positive or negative in polarity.

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