Detection of Fake News Using Deep Learning and Machine Learning - Gabriela CHIRIAC; Ada Maria CATINA (Database Systems Journal, 2025)
Automatically identifying fake news is a complex challenge requiring detailed understanding of misinformation propagation and advanced data processing. Machine Learning and Deep Learning algorithms for detection demand continuous adaptation as disinformation tactics evolve. While promising, these technologies must be carefully calibrated for different contexts. This paper explores automated fake-news detection methods, analyzing their effectiveness and proposing improvements to address data quality, domain variability, and evolving disinformation strategies.