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Combating Fake News with Computational Intelligence Techniques

This book presents the latest cutting-edge research, theoretical methods, and novel applications in the field of computational intelligence techniques and methods for combating fake news. Fake news is everywhere. Despite the efforts of major social network players such as Facebook and Twitter to fight disinformation, miracle cures and conspiracy theories continue to rain down on the net. Artificial intelligence can be a bulwark against the diversity of fake news on the Internet and social networks. This book discusses new models, practical solutions, and technological advances related to detecting and analyzing fake news based on computational intelligence models and techniques, to help decision-makers, managers, professionals, and researchers design new paradigms considering the unique opportunities associated with computational intelligence techniques. Further, the book helps readers understand computational intelligence techniques combating fake news in a systematic and straightforward way.

[15] stated, fake news publishers usually have an intent to mislead the reader and influence a larger group of people, and for that purpose, a specific style of writing is used, thus it is reasonable to make use of linguistic features ...

Detecting Fake News on Social Media

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/

Style approaches try to detect fake news by capturing the manipulators in the writing style of the news content. ... Moreover, other features can be specifically designed to capture the deceptive cues in writing styles to differentiate ...

Research Anthology on Fake News, Political Warfare, and Combatting the Spread of Misinformation

With recent headlines around fake news from world leaders and around presidential elections, Twitter and other social media platforms being pressured to detect and label misinformation posted on their platforms, as well as misinformation around COVID-19 and its vaccine, the world has seen an increase in protests, policy changes, and even chaos surrounding this information. This spread of misinformation, when left unchecked, can turn fiction into fact and result in a mass misconception of the truth that shapes opinions, creates false narratives, and impacts multiple facets of society in potentially detrimental ways, indicating a need for the latest research on how the devastating impacts of this trend, how to discern facts from misinformation, as well as more information on technological advancements in fake news detection The Research Anthology on Fake News, Political Warfare, and Combatting the Spread of Misinformation is a compilation of the most comprehensive, previously published, and highly cited research from prestigious institutions including Columbia University and Stanford University, USA, which focuses on understanding fake news, how it spreads, its negative effects, and current solutions being investigated. While highlighting topics such as fake news, trending conspiracy theories, media distrust, political warfare, and detection methods, this book is ideally intended for practitioners, stakeholders, researchers, academicians, and students interested in the continuing surge of fake news and its, at times, dangerous results.

ML and NLP techniques can be used to analyze diverse features of trolls (in contrast to legitimate users), using writing style, sentiment, behaviors, social interactions, linked media and publication time, in order to automatically ...

Navigating Fake News, Alternative Facts, and Misinformation in a Post-Truth World

In the current day and age, objective facts have less influence on opinions and decisions than personal emotions and beliefs. Many individuals rely on their social networks to gather information thanks to social media’s ability to share information rapidly and over a much greater geographic range. However, this creates an overall false balance as people tend to seek out information that is compatible with their existing views and values. They deliberately seek out “facts” and data that specifically support their conclusions and classify any information that contradicts their beliefs as “false news.” Navigating Fake News, Alternative Facts, and Misinformation in a Post-Truth World is a collection of innovative research on human and automated methods to deter the spread of misinformation online, such as legal or policy changes, information literacy workshops, and algorithms that can detect fake news dissemination patterns in social media. While highlighting topics including source credibility, share culture, and media literacy, this book is ideally designed for social media managers, technology and software developers, IT specialists, educators, columnists, writers, editors, journalists, broadcasters, newscasters, researchers, policymakers, and students.

ML and NLP techniques can be used to analyze diverse features of trolls (in contrast to legitimate users), using writing style, sentiment, behaviors, social interactions, linked media and publication time, in order to automatically ...