This book provides an overview of fake news detection, both through a variety of tutorial-style survey articles that capture advancements in the field from various facets and in a somewhat unique direction through expert perspectives from various disciplines. The approach is based on the idea that advancing the frontier on data science approaches for fake news is an interdisciplinary effort, and that perspectives from domain experts are crucial to shape the next generation of methods and tools. The fake news challenge cuts across a number of data science subfields such as graph analytics, mining of spatio-temporal data, information retrieval, natural language processing, computer vision and image processing, to name a few. This book will present a number of tutorial-style surveys that summarize a range of recent work in the field. In a unique feature, this book includes perspective notes from experts in disciplines such as linguistics, anthropology, medicine and politics that will help to shape the next generation of data science research in fake news. The main target groups of this book are academic and industrial researchers working in the area of data science, and with interests in devising and applying data science technologies for fake news detection. For young researchers such as PhD students, a review of data science work on fake news is provided, equipping them with enough know-how to start engaging in research within the area. For experienced researchers, the detailed descriptions of approaches will enable them to take seasoned choices in identifying promising directions for future research.
How Users Process Information about Science, Health, and Technology
Author: Ronald A. Yaros
Category: Social Science
This book explores how individuals process important but complex news about science, health and technology. The research measures the relationships of new media, its content and its audiences. Specifically, how does the non-linear freedom of hypertext affect interest in and comprehension of news about complex topics? In the first of two experiments, reading comprehension theory from the Structure Building Framework (Gernsbacher, 1990) and the Construction-Integration Model (van Dyk & Kintsch, 1983) are synthesized with the theoretical role of situational interest in learning from text (Hidi, 1988). Experiment two tests the same content from experiment one in a non-linear hypertext environment to measure how message structure affects interest and understanding.
A History of Data Graphics in News and Communications
Author: Murray Dick
Publisher: MIT Press
An exploration of infographics and data visualization as a cultural phenomenon, from eighteenth-century print culture to today's data journalism. Infographics and data visualization are ubiquitous in our everyday media diet, particularly in news—in print newspapers, on television news, and online. It has been argued that infographics are changing what it means to be literate in the twenty-first century—and even that they harmonize uniquely with human cognition. In this first serious exploration of the subject, Murray Dick traces the cultural evolution of the infographic, examining its use in news—and resistance to its use—from eighteenth-century print culture to today's data journalism. He identifies six historical phases of infographics in popular culture: the proto-infographic, the classical, the improving, the commercial, the ideological, and the professional. Dick describes the emergence of infographic forms within a wider history of journalism, culture, and communications, focusing his analysis on the UK. He considers their use in the partisan British journalism of late eighteenth and early nineteenth-century print media; their later deployment as a vehicle for reform and improvement; their mass-market debut in the twentieth century as a means of explanation (and sometimes propaganda); and their use for both ideological and professional purposes in the post–World War II marketized newspaper culture. Finally, he proposes best practices for news infographics and defends infographics and data visualization against a range of criticism. Dick offers not only a history of how the public has experienced and understood the infographic, but also an account of what data visualization can tell us about the past.
How can we keep up with the deluge of information about COVID-19 and tell which parts are most important and trustworthy?We read: 'Scientists recommend', 'Experts warn', 'A new model predicts'. How do scientific experts come up with their recommendations? What do their predictions really mean for us, for our friends, and our families?How can we make rational decisions? And how can we have sensible conversations about the pandemic when we disagree?These are the questions that this book is trying to address.It is written in the form of dialogues. Alice, a student of epidemiology, explains the science to three of her fellow students who have a lot of questions for her. The students have the same concerns that we all share to varying degrees: What the pandemic is doing to our health, our economy, and our cherished freedoms. In their conversations, they discover how the science relates to these questions.The book focuses on epidemiology, the science of how infections spread and how the spread can be mitigated. The science of how many infections can be prevented by certain kinds of actions. This is what we need to understand if we want to act wisely, as individuals and as a society.The author's goal is to help the reader think about the COVID-19 pandemic like an epidemiologist. About the various preventive measures, what they are trying to accomplish, what the obstacles are. About what is likely to be most effective in the long run at moderate economic and personal cost. About the likely consequences of personal decisions. About how to best protect oneself and others while allowing all of us to lead lives that are as close as possible to normal.While some chapters present slightly more advanced material than others, no scientific background is needed to follow the conversations. The technical concepts are explained in small steps and the occasional calculations in the book require only high-school mathematics.
This book explores the challenges that disinformation, fake news, and post-truth politics pose to democracy from a multidisciplinary perspective. The authors analyse and interpret how the use of technology and social media as well as the emergence of new political narratives has been progressively changing the information landscape, undermining some of the pillars of democracy. The volume sheds light on some topical questions connected to fake news, thereby contributing to a fuller understanding of its impact on democracy. In the Introduction, the editors offer some orientating definitions of post-truth politics, building a theoretical framework where various different aspects of fake news can be understood. The book is then divided into three parts: Part I helps to contextualise the phenomena investigated, offering definitions and discussing key concepts as well as aspects linked to the manipulation of information systems, especially considering its reverberation on democracy. Part II considers the phenomena of disinformation, fake news, and post-truth politics in the context of Russia, which emerges as a laboratory where the phases of creation and diffusion of fake news can be broken down and analysed; consequently, Part II also reflects on the ways to counteract disinformation and fake news. Part III moves from case studies in Western and Central Europe to reflect on the methodological difficulty of investigating disinformation, as well as tackling the very delicate question of detection, combat, and prevention of fake news. This book will be of great interest to students and scholars of political science, law, political philosophy, journalism, media studies, and computer science, since it provides a multidisciplinary approach to the analysis of post-truth politics.