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A web app for displaying emotion in trending tweets across the world. Used Twitter API to download an emotion annotated data set of 0.47 million tweets. Trained a multi-class classifier and using the generated model classify real-time tweets.

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gauravahuja/twitter_emotion_visualization

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For Documentation see ./api_doc

In app.py fill in the values for the following variables by creating an app on Twitter

  1. consumer_key
  2. consumer_secret
  3. access_key
  4. access_token_secret

Installation Steps

  1. Clone the repository

git clone [email protected]:gauravahuja/twitter_emotion_visualization.git cd twitter_emotion_visualization

  1. Intialize and activate a virtual environment

virtualenv venv source venv/bin/activate

  1. Install the dependencies

pip install -r requirements.txt

  1. Run the development server

python app.py

  1. Navigate to http://localhost:5000

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A web app for displaying emotion in trending tweets across the world. Used Twitter API to download an emotion annotated data set of 0.47 million tweets. Trained a multi-class classifier and using the generated model classify real-time tweets.

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