This app currently takes a Twitter user's news feed and evaluates the extent to which the articles they share agree or disagree with articles published by six major news outlets.
It uses a classification algorithm developed by UKP Lab (https://github.com/hanselowski/athene_system)
==================================
Install python3. Clone this repository. Create virtual environment.
python3 -m venv myvenv source venv/bin/activate
Install requirements.
git clone "https://github.com/hanselowski/athene_system.git" python3 pip install -r requirements.txt
Edit feed_compare/tokens_SKELETON.py to include relevant Twitter tokens (Consumer Key, Secret, and Access Token), and rename to tokens.py.
Unzip the features file to the directory:
athene_system/data/fnc-1/features
Unzip the model file to the directory:
athene_system/data/fnc-1/mlp_models
Parts of the Natural Language Toolkit (NLTK) might need to be installed manually:
python3 -c "import nltk; nltk.download('stopwords'); nltk.download('punkt'); nltk.download('wordnet')"
Optional: Copy Word2Vec GoogleNews-vectors-negative300.bin.gz to folder athene_system/data/embeddings/google_news/.
Optional: Download Paraphrase Database: Lexical XL Paraphrases 1.0 and extract it to the athene_system/data/ppdb folder.
==================================
python app.py
Browse to http://localhost:5001/