Misinformation Detection

In an era when misinformation spreads faster than ever, cutting-edge statistical and machine learning techniques offer a powerful defense. This book provides a rigorous, technical deep dive into misinformation detection, combining statistical modeling, signal processing, and machine learning to tackle false information across digital media.

Beginning with an overview of the role of statistics in detecting misinformation, the book explores latent variable models, independent vector analysis, semi-supervised learning, and multimodal fusion. In that way, the book offers advanced yet practical methodologies for real-world applications.

A dedicated section on system integration and deployment focuses on how these techniques can move beyond theory into actionable solutions, covering explainability, evaluation, and human-in-the-loop aspects. The book also critically examines the social, ethical, and financial implications of misinformation, and provides insights into policy challenges and freedom of expression concerns.