[PDF] Detecting Fake News On Social Media eBook

Author : Kai Shu
Publisher : Springer Nature
Page : 121 pages
File Size : 16,54 MB
Release : 2022-05-31
Category : Computers
ISBN : 3031019156

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In the past decade, social media has become 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 area that is attracting tremendous attention. This book, from a data mining perspective, introduces the basic concepts and characteristics of fake news across disciplines, reviews representative fake news detection methods in a principled way, and illustrates challenging issues of fake news detection on social media. In particular, we discussed the value of news content and social context, and important extensions to handle early detection, weakly-supervised detection, and explainable detection. The concepts, algorithms, and methods described in this lecture can help harness the power of social media to build effective and intelligent fake news detection systems. This book is an accessible introduction to the study of detecting fake news on social media. It is an 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. The readers are encouraged to visit the book website for the latest information: http://dmml.asu.edu/dfn/

Author : Wamuyu, Patrick Kanyi
Publisher : IGI Global
Page : 358 pages
File Size : 13,23 MB
Release : 2020-10-16
Category : Computers
ISBN : 1799847195

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Social media has revolutionized how individuals, communities, and organizations create, share, and consume information. Similarly, social media offers numerous opportunities as well as enormous social and economic ills for individuals, communities, and organizations. Despite the increase in popularity of social networking sites and related digital media, there are limited data and studies on consumption patterns of the new media by different global communities. Analyzing Global Social Media Consumption is an essential reference book that investigates the current trends, practices, and newly emerging narratives on theoretical and empirical research on all aspects of social media and its global use. Covering topics that include fake news detection, social media addiction, and motivations and impacts of social media use, this book is ideal for big data analysts, media and communications experts, researchers, academicians, and students in media and communications, information systems, and information technology study programs.

Author : Rainer Greifeneder
Publisher : Routledge
Page : 222 pages
File Size : 50,85 MB
Release : 2020-08-13
Category : Language Arts & Disciplines
ISBN : 1000179052

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This volume examines the phenomenon of fake news by bringing together leading experts from different fields within psychology and related areas, and explores what has become a prominent feature of public discourse since the first Brexit referendum and the 2016 US election campaign. Dealing with misinformation is important in many areas of daily life, including politics, the marketplace, health communication, journalism, education, and science. In a general climate where facts and misinformation blur, and are intentionally blurred, this book asks what determines whether people accept and share (mis)information, and what can be done to counter misinformation? All three of these aspects need to be understood in the context of online social networks, which have fundamentally changed the way information is produced, consumed, and transmitted. The contributions within this volume summarize the most up-to-date empirical findings, theories, and applications and discuss cutting-edge ideas and future directions of interventions to counter fake news. Also providing guidance on how to handle misinformation in an age of “alternative facts”, this is a fascinating and vital reading for students and academics in psychology, communication, and political science and for professionals including policy makers and journalists.

Author : Kai Shu
Publisher : Springer Nature
Page : 285 pages
File Size : 30,39 MB
Release : 2020-06-17
Category : Computers
ISBN : 3030426998

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This book serves as a convenient entry point for researchers, practitioners, and students to understand the problems and challenges, learn state-of-the-art solutions for their specific needs, and quickly identify new research problems in their domains. The contributors to this volume describe the recent advancements in three related parts: (1) user engagements in the dissemination of information disorder; (2) techniques on detecting and mitigating disinformation; and (3) trending issues such as ethics, blockchain, clickbaits, etc. This edited volume will appeal to students, researchers, and professionals working on disinformation, misinformation and fake news in social media from a unique lens.

Author : Hemant Kumar Soni
Publisher : CRC Press
Page : 325 pages
File Size : 50,5 MB
Release : 2024-08-21
Category : Computers
ISBN : 104010049X

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Identifying and stopping the dissemination of fabricated news, hate speech, or deceptive information camouflaged as legitimate news poses a significant technological hurdle. This book presents emergent methodologies and technological approaches of natural language processing through machine learning for counteracting the spread of fake news and hate speech on social media platforms. • Covers various approaches, algorithms, and methodologies for fake news and hate speech detection. • Explains the automatic detection and prevention of fake news and hate speech through paralinguistic clues on social media using artificial intelligence. • Discusses the application of machine learning models to learn linguistic characteristics of hate speech over social media platforms. • Emphasizes the role of multilingual and multimodal processing to detect fake news. • Includes research on different optimization techniques, case studies on the identification, prevention, and social impact of fake news, and GitHub repository links to aid understanding. The text is for professionals and scholars of various disciplines interested in fake news and hate speech detection.

Author : Huan Liu
Publisher : Chapman & Hall/CRC
Page : 300 pages
File Size : 50,38 MB
Release : 2010
Category : Computers
ISBN : 9781420083309

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This book begins with a brief introduction to social computing and a review of classic graph theory and game theory. It then examines the data used to construct social networks, focusing on emerging Web 2.0 technologies and social networking websites, such as Facebook and MySpace. The book also explores data mining for social network extraction and analysis, presenting link and graph mining algorithms, such as subgraph discovery and clustering. In the last section, the authors provide case studies to illustrate concepts and principles as well as to demonstrate how to integrate components in order to solve real-world problems.

Author : Patricia Moravec
Publisher :
Page : 0 pages
File Size : 31,73 MB
Release : 2018
Category :
ISBN :

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Fake news (i.e., misinformation) on social media has sharply increased over the past years. We conducted an experiment collecting behavioral and EEG data from 83 social media users to understand whether they could detect fake news on social media, and the factors affecting cognition and judgment. We found that confirmation bias dominates, with most users unable to distinguish real news from fake. Users exhibit greater cognitive activity when news headlines align with their political opinions, and they are more likely to believe them. Headlines that challenge their opinions receive little cognitive activity (i.e., they are ignored) and users are less likely to believe them. The presence of a fake news flag on a headline aligned with users' opinions triggered cognitive activity that could be associated with increased semantic memory retrieval, false memory construction, or increased attention. However, this flag had no effect on judgments about truth; flagging headlines as false did not influence users' beliefs. Only 17% of our participants could detect fake news better than chance, with only one detecting fake news more than 60% of the time. In other words, most social media users would make better truth judgments by flipping a coin.

Author : Tatiana Antipova
Publisher : Springer Nature
Page : 414 pages
File Size : 43,89 MB
Release : 2020-05-26
Category : Computers
ISBN : 3030492648

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This book presents the proceedings of the 2020 International Conference on Integrated Science in Digital Age, which was jointly supported by the Institute of Certified Specialists (Russia) and Springer, and was held on May 1–3, 2020. The conference provided an international forum for researchers and practitioners to present and discuss the latest innovations, trends, results, experiences and concerns in the various areas of integrated science in the digital age. The main goal of the conference was to efficiently disseminate original findings in the natural and social sciences, covering topics such as blockchain & cryptocurrency; computer law & security; digital accounting & auditing; digital business & finance; digital economics; digital education; digital engineering; machine learning; smart cities in the digital age; health policy & management; and information management.

Author : Deepak P
Publisher : Springer Nature
Page : 302 pages
File Size : 50,86 MB
Release : 2021-04-29
Category : Computers
ISBN : 3030626962

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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.

Author : Amanda Sturgill
Publisher : Rowman & Littlefield
Page : 161 pages
File Size : 38,34 MB
Release : 2020-08-20
Category : Language Arts & Disciplines
ISBN : 1538141043

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Teaching fact checking and verification is an essential part of journalism education. When a confusing media environment includes statements like “Truth is not truth” and “The president offered alternative facts,” students need to go beyond traditional reporting standards. They need to be trained to consider the presentation of reality in deciding if a statement is misleading or patently false. Detecting Deception applies the concepts of logical argumentation to supplement the verification techniques that are the stock and trade of any media professional. Pithy and practical, Amanda Sturgill draws from present day news examples to help students recognize the most common bad arguments people make. Detecting Deception is an essential tool for training future journalists to build stories that recognize faulty arguments and hold their subjects to a higher standard.