LingML: Linguistic-Informed Machine Learning for Enhanced Fake News Detection

arXiv:2405.04165v1 Announce Type: new
Abstract: Nowadays, Information spreads at an unprecedented pace in social media and discerning truth from misinformation and fake news has become an acute societal challenge. Machine learning (ML) models have been employed to identify fake news but are far from perfect with challenging problems like limited accuracy, interpretability, and generalizability. In this paper, we enhance ML-based solutions with linguistics input and we propose LingML, linguistic-informed ML, for fake news detection. We conducted an experimental study with …

abstract accuracy arxiv become challenge cs.cl detection fake fake news identify information machine machine learning media misinformation social social media truth type