Fake News Detection Using Data Analytics - Egboh, Daniel
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In an era where misinformation spreads rapidly online, Fake News Detection Using Data Analytics offers a comprehensive guide to identifying and combating fake news through advanced data-driven techniques. This book explores key concepts in machine learning, natural language processing, and network analysis to detect false information across social media and news platforms. Readers will learn how to collect, pre-process, and analyse data, build effective fake news detection models, and implement real-time monitoring systems. With practical case studies and insights into ethical challenges, this…mehr

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Produktbeschreibung
In an era where misinformation spreads rapidly online, Fake News Detection Using Data Analytics offers a comprehensive guide to identifying and combating fake news through advanced data-driven techniques. This book explores key concepts in machine learning, natural language processing, and network analysis to detect false information across social media and news platforms. Readers will learn how to collect, pre-process, and analyse data, build effective fake news detection models, and implement real-time monitoring systems. With practical case studies and insights into ethical challenges, this book is an essential resource for data scientists, journalists, and anyone interested in preserving the integrity of information in the digital world.
Autorenporträt
Daniel Egboh is a Nigerian-born Data Scientist with a passion for Technological Innovation. He holds a Bachelor's Degree in Computer Science and a Master's Degree in Big Data Science and Technology from the Prestigious University of Bradford, UK. Daniel specializes in leveraging data to drive impactful solutions focusing on big data technologies.