Fake News in Context defines fake news and sets it within a historical and international context. Helping readers to become more skilled at detecting misinformation, the book also demonstrates how such knowledge can be leveraged to facilitate more effective engagement in civic education. Distinguishing between fake news and other forms of misinformation, the book explains the complete communication cycle of fake news: how and why it is created, disseminated and accessed. The book then explains the physical and psychological reasons why people believe fake news. Providing generic methods for identifying fake news, Farmer also explains the use of fact- checking tools and automated algorithms. The book then details how various literacies, including news, media, visual, information, digital and data, offer unique concepts and skills that can help interpret fake news. Arguing that individuals and groups can respond and counter fake news, which leads to civic engagement and digital citizenship, the book concludes by providing strategies for instruction and tips for collaborating with librarians. Including a range of international examples, Fake News in Context will be of interest to teaching faculty, and students of library and information science, communication studies, media studies, politics and journalism. Librarians and information professionals will also find a valuable resource in this book.
The Roots of Fake News argues that 'fake news' is not a problem caused by the power of the internet, or by the failure of good journalism to assert itself. Rather, it is within the news's ideological foundations - professionalism, neutrality, and most especially objectivity - that the true roots of the current 'crisis' are to be found. Placing the concept of media objectivity in a fuller historical context, this book examines how current perceptions of a crisis in journalism actually fit within a long history of the ways news media have avoided, obscured, or simply ignored the difficulties involved in promising objectivity, let alone 'truth'. The book examines journalism's relationships with other spheres of human endeavour (science, law, philosophy) concerned with the pursuit of objective truth, to argue that the rising tide of 'fake news' is not an attack on the traditional ideologies which have supported journalism. Rather, it is an inevitable result of their inherent flaws and vulnerabilities. This is a valuable resource for students and scholars of journalism and history alike who are interested in understanding the historical roots, and philosophical context of a fiercely contemporary issue.
This book is an accessible introduction to the study of detecting fake news on social media. The concepts, algorithms, and methods described in this book can help harness the power of social media to build effective and intelligent fake news detection systems. In the past decade, social media is becoming increasingly popular for news consumption due to its easy access, fast dissemination, and low cost. However, social media also enables the wide propagation of "fake news," i.e., news with intentionally false information. Fake news on social media can have significant negative societal effects. Therefore, fake news detection on social media has recently become an emerging research that is attracting tremendous attention. From a data mining perspective, this book introduces the basic concepts and characteristics of fake news across disciplines, reviews representative fake news detection methods in a principled way, and illustrates advanced settings of fake news detection on social media. In particular, the authors discuss the value of news content and social context, as well as important extensions to handle early detection, weakly-supervised detection, and explainable detection. This is essential reading for students, researchers, and practitioners to understand, manage, and excel in this area. This book is supported by additional materials, including lecture slides, the complete set of figures, key references, datasets, tools used in this book, and the source code of representative algorithms.
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