Fake News Detection in Internet Using Deep Learning: A Review

Barrutia-Barreto I.; Seminario-Córdova R.; Chero-Arana B. · Studies in Computational Intelligence (2022) · DOI: 10.1007/978-3-030-90087-8_3

Resumen

The main objective of this research was to explore, from a reflexivity approach, the current state of Deep learning techniques for automatic detection of fake news on the Internet, analyzing the most important Deep learning algorithms and studies on their effectiveness in detecting distrustful information. The research methodology employed was bibliographic, documentary and descriptive. The information was collected from several scientific articles provided by indexed journals and web platforms, using keywords such as “fake news”, “Deep learning” and “neural networks” for the compilation. As a result of this research, it was concluded that Deep learning techniques present a better performance than conventional methods and will be of great importance in the future of war against fake news due to their potential in automatic detection.