Why People Believe Fake News: Cognitive Biases, NLP Detection Models, and Post Truth Dynamics

Abstract

The rapid growth of digital media has reshaped how people encounter, evaluate, and share information. As a result, misleading narratives circulate widely and influence public perception even when factual evidence is available. This work examines the reasons people believe false information, with a focus on cognitive biases, emotional triggers, and the influence of social identity. It also analyzes recent natural language processing models designed for misinformation detection and discusses how post truth dynamics amplify the spread of fabricated stories. The study integrates behavioral insight with machine learning methods to provide an interdisciplinary view of the challenge.