Sagnik07 / Fake-News-Identification

In this repository, we propose different machine learning and deep learning models for identification of fake news in online media.

deep-learning logistic-regression lstm natural-language-processing streamlit svm

Fake News Detection (Team 18)

To Run (training):

Save the NELA-GT 2019 dataset in Google Drive
Run Experiments-jupyter/Fake-News.ipynb (change paths to match)

To Run (testing samples):

Install the requirements from streamlit/requirements.txt
Save the corresponding testing files from training as joblib files
Run 'streamlit run visualizer.py' (change paths if needed)

Best Performing Model: TF-IDF Vectors with SVM (90.6%)

Original Notebook links:

About

In this repository, we propose different machine learning and deep learning models for identification of fake news in online media.

deep-learning logistic-regression lstm natural-language-processing streamlit svm

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Language:Jupyter Notebook 99.7%Language:TeX 0.2%Language:Python 0.0%