Detecting Fake News On Social Media
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Detecting Fake News On Social Media
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Author : Kai Shu
language : en
Publisher: Springer Nature
Release Date : 2022-05-31
Detecting Fake News On Social Media written by Kai Shu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-31 with Computers categories.
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/
Detecting Fake News On Social Media
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Author : Kai Shu
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2019-07-03
Detecting Fake News On Social Media written by Kai Shu and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-03 with Computers categories.
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.
Disinformation Misinformation And Fake News In Social Media
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Author : Kai Shu
language : en
Publisher: Springer Nature
Release Date : 2020-06-17
Disinformation Misinformation And Fake News In Social Media written by Kai Shu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-17 with Computers categories.
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.
Analyzing Global Social Media Consumption
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Author : Wamuyu, Patrick Kanyi
language : en
Publisher: IGI Global
Release Date : 2020-10-16
Analyzing Global Social Media Consumption written by Wamuyu, Patrick Kanyi and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-16 with Computers categories.
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.
Combating Fake News With Computational Intelligence Techniques
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Author : Mohamed Lahby
language : en
Publisher: Springer Nature
Release Date : 2021-12-15
Combating Fake News With Computational Intelligence Techniques written by Mohamed Lahby and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-15 with Technology & Engineering categories.
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.
Text And Social Media Analytics For Fake News And Hate Speech Detection
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Author : Hemant Kumar Soni
language : en
Publisher:
Release Date : 2024-08-21
Text And Social Media Analytics For Fake News And Hate Speech Detection written by Hemant Kumar Soni and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-21 with Computers categories.
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 speeches 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 GiT Hub repository links to aid understanding The text is for professionals and scholars of various disciplines interested in fake news and hate speech detection.
Data Science For Fake News
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Author : Deepak P
language : en
Publisher: Springer Nature
Release Date : 2021-04-29
Data Science For Fake News written by Deepak P and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-29 with Computers categories.
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.
Fake News In An Era Of Social Media
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Author : Yasmin Ibrahim
language : en
Publisher: Rowman & Littlefield
Release Date : 2020-01-29
Fake News In An Era Of Social Media written by Yasmin Ibrahim and has been published by Rowman & Littlefield this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-29 with Social Science categories.
Over the last few years, social media has expanded to become a key platform for news dissemination and circulation, and a key orginator and propogator of 'fake news'.. Nations, governments, organisations and societies are now coming to terms with the unpredictable and debilitating consequences of fake news. The propagation of news containing falsehoods has been linked to an increase in measles cases, surges in youth crimes, the spread of pseudo-science, compromised national security, and more. Some even perceive it as a global threat to democratic systems around the world. In this book, the authors examine factors influencing the spread of fake news, and suggest ways to combat it by exploring the key elements which enable and facilitate this phenomenon.
An Approach For Improving The Accuracy For Detecting Fake Tweets
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Author : Vaishali Vaibhav Hirlekar
language : en
Publisher: Mohammed Abdul Sattar
Release Date : 2024-01-31
An Approach For Improving The Accuracy For Detecting Fake Tweets written by Vaishali Vaibhav Hirlekar and has been published by Mohammed Abdul Sattar this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-31 with Computers categories.
In the modern world, fake information is a growing issue. Hoaxes and deliberate lies are disseminated through traditional media outlets or social platforms can be considered misleading/fake news. Fake information is produced and spread to deceive a person or an organization financially or politically. The transmission and dissemination of such misleading information could cause serious hazards; it could create threat to national security too. To mitigate the negative consequences of misleading news, a method to automatically recognise fake news must be developed. So far different measures have been put in order to identify misleading information. There are various ways to characterise fake news. An article of news that is purposefully and demonstrably untrue is known as fake news. The phrase "fake news" is used to describe misleading information that appears in mainstream media. Fake news is a term that is used to describe a variety of ideas, including rumour and misinformation. According to another definition, fake news is a type of misleading information released under the guise of being legitimate news commonly spread through news outlets or the internet with a goal to gain politically or financially, boost reading, and prejudice public opinion. Some made distinctions between different types of fake news, such as severe fabrications, massive hoaxes, and hilarious fakes. Today, social media has become a necessary component of daily life. Every day, we read numerous articles on social media. Some are real, but majority of the time they are found fake. The reason behind this is, every user is a self-publisher here, who doesn't verify the veracity of the information and people forward the erroneous or incorrect information further which is composed of fabricated articles which ultimately results in fake news, those stories are made up to sway readers' judgments or mislead them. Because of this misleading information are spread online more quickly than we can ever conceive, they have become more prevalent over the past several years on social platforms. Plenty of disinformation is spread about issues like politics, economics, and technological advancements. Misinformation, disinformation, malinformation are three distinct concepts that are frequently discussed in fake news. Despite being fake, misinformation is something which is being shared unintentionally. Disinformation is when a person deliberately spreads false information after knowing it to be real. Contrarily, information that is grounded in reality but does harm to an individual, group, or nation is referred to as malinformation.
Deep Learning Techniques And Optimization Strategies In Big Data Analytics
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Author : Thomas, J. Joshua
language : en
Publisher: IGI Global
Release Date : 2019-11-29
Deep Learning Techniques And Optimization Strategies In Big Data Analytics written by Thomas, J. Joshua and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-29 with Computers categories.
Many approaches have sprouted from artificial intelligence (AI) and produced major breakthroughs in the computer science and engineering industries. Deep learning is a method that is transforming the world of data and analytics. Optimization of this new approach is still unclear, however, and there’s a need for research on the various applications and techniques of deep learning in the field of computing. Deep Learning Techniques and Optimization Strategies in Big Data Analytics is a collection of innovative research on the methods and applications of deep learning strategies in the fields of computer science and information systems. While highlighting topics including data integration, computational modeling, and scheduling systems, this book is ideally designed for engineers, IT specialists, data analysts, data scientists, engineers, researchers, academicians, and students seeking current research on deep learning methods and its application in the digital industry.