Leveraging Machine Learning for Fake News Detection

Elio Masciari, Vincenzo Moscato, Antonio Picariello, Giancarlo Sperlì

2020

Abstract

The uncontrolled growth of fake news creation and dissemination we observed in recent years causes continuous threats to democracy, justice, and public trust. This problem has significantly driven the effort of both academia and industries for developing more accurate fake news detection strategies. Early detection of fake news is crucial, however the availability of information about news propagation is limited. Moreover, it has been shown that people tend to believe more fake news due to their features (Vosoughi et al., 2018). In this paper, we present our complete framework for fake news detection and we discuss in detail a solution based on machine learning. Our experiments conducted on two well-known and widely used real-world datasets suggest that our settings can outperform the state-of-the-art approaches and allows fake news accurate detection, even in the case of limited content information.

Paper Citation

in Harvard Style

Masciari E., Moscato V., Picariello A. and Sperlì G. (2020). Leveraging Machine Learning for Fake News Detection.In Proceedings of the 9th International Conference on Data Science, Technology and Applications - Volume 1: DATA, ISBN 978-989-758-440-4, pages 151-157. DOI: 10.5220/0009767401510157

in Bibtex Style

@conference{data20,
author={Elio Masciari and Vincenzo Moscato and Antonio Picariello and Giancarlo Sperlì},
title={Leveraging Machine Learning for Fake News Detection},
booktitle={Proceedings of the 9th International Conference on Data Science, Technology and Applications - Volume 1: DATA,},
year={2020},
pages={151-157},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009767401510157},
isbn={978-989-758-440-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 9th International Conference on Data Science, Technology and Applications - Volume 1: DATA,
TI - Leveraging Machine Learning for Fake News Detection
SN - 978-989-758-440-4
AU - Masciari E.
AU - Moscato V.
AU - Picariello A.
AU - Sperlì G.
PY - 2020
SP - 151
EP - 157
DO - 10.5220/0009767401510157