Misinformation Detection
A Signal Processing and Machine Learning Perspective
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Beschreibung
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.
In addition, this book:
- Describes ways to filter out false or misleading information to help people stay well-informed and make good decisions
- Explains how statistical and machine learning techniques are used to tackle false information across digital media
- Provides technical information and practical insights that are useful to academic and industry professionals
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.
Describes ways to filter out false or misleading information to help people stay well-informed and make good decisions Explains how statistical and machine learning techniques are used to tackle false information across digital media Provides technical information and practical insights that are useful to academic and industry professionals
Autor*in
Roberto Corizzo
Themen in »Misinformation Detection«
misinformation detection fake news classification signal processing in misinformation detection machine learning in misinformation detection graph signal processing frequency domain analysis source separation techniques image and video forensics