Raising a Model for Fake News Detection Using Machine Learning in Python

Author:

Agudelo Gerardo Ernesto Rolong,Parra Octavio José Salcedo,Velandia Julio Barón

Publisher

Springer International Publishing

Reference14 articles.

1. Allcott, H., Gentzkow, M.: Social media and fake news in the 2016 election. J. Econ. Perspect. 31(2—Spring), 211–236 (2017). http://doi.org/10.1257/jep.31.2.211

2. Bajaj, S.: The Pope Has a New Baby! Fake news detection using deep learning (n.d.). Retrieved from https://web.stanford.edu/class/cs224n/reports/2710385.pdf

3. Bourgonje, P., Schneider, J.M., Rehm, G.: From Clickbait to fake news detection: an approach based on detecting the stance of headlines to articles, 84–89 (2017). Retrieved from http://www.aclweb.org/anthology/W/W17/W17-4215.pdf

4. Chaudhry, A.K., Baker, D., Thun-Hohenstein, P.: Stance detection for the fake news challenge: identifying textual relationships with deep neural nets (n.d.). Retrieved from https://web.stanford.edu/class/cs224n/reports/2760230.pdf

5. Chiu, J., Gokcen, A., Wang, W., Yan, X.: Classification of fake and real articles based on support vector machines (n.d.). Retrieved from https://pdfs.semanticscholar.org/05be/61a7726916644e49e578378d4faa7aa5f4ce.pdf

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