Data Science For Fake News

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Data Science for Fake News

Author : Deepak P
Publisher : Springer Nature
ISBN 13 : 3030626962
Total Pages : 302 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis Data Science for Fake News by : Deepak P

Download or read book Data Science for Fake News written by Deepak P and published by Springer Nature. This book was released on 2021-04-29 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Data Science for Fake News

Author : Deepak P
Publisher : Springer Nature
ISBN 13 : 3030626962
Total Pages : 302 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis Data Science for Fake News by : Deepak P

Data Preprocessing, Active Learning, and Cost Perceptive Approaches for Resolving Data Imbalance

Author : Rana, Dipti P.
Publisher : IGI Global
ISBN 13 : 1799873730
Total Pages : 309 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Data Preprocessing, Active Learning, and Cost Perceptive Approaches for Resolving Data Imbalance by : Rana, Dipti P.

Download or read book Data Preprocessing, Active Learning, and Cost Perceptive Approaches for Resolving Data Imbalance written by Rana, Dipti P. and published by IGI Global. This book was released on 2021-06-04 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the last two decades, researchers are looking at imbalanced data learning as a prominent research area. Many critical real-world application areas like finance, health, network, news, online advertisement, social network media, and weather have imbalanced data, which emphasizes the research necessity for real-time implications of precise fraud/defaulter detection, rare disease/reaction prediction, network intrusion detection, fake news detection, fraud advertisement detection, cyber bullying identification, disaster events prediction, and more. Machine learning algorithms are based on the heuristic of equally-distributed balanced data and provide the biased result towards the majority data class, which is not acceptable considering imbalanced data is omnipresent in real-life scenarios and is forcing us to learn from imbalanced data for foolproof application design. Imbalanced data is multifaceted and demands a new perception using the novelty at sampling approach of data preprocessing, an active learning approach, and a cost perceptive approach to resolve data imbalance. Data Preprocessing, Active Learning, and Cost Perceptive Approaches for Resolving Data Imbalance offers new aspects for imbalanced data learning by providing the advancements of the traditional methods, with respect to big data, through case studies and research from experts in academia, engineering, and industry. The chapters provide theoretical frameworks and the latest empirical research findings that help to improve the understanding of the impact of imbalanced data and its resolving techniques based on data preprocessing, active learning, and cost perceptive approaches. This book is ideal for data scientists, data analysts, engineers, practitioners, researchers, academicians, and students looking for more information on imbalanced data characteristics and solutions using varied approaches.

Data Science: From Research to Application

Author : Mahdi Bohlouli
Publisher : Springer Nature
ISBN 13 : 3030373096
Total Pages : 350 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Data Science: From Research to Application by : Mahdi Bohlouli

Download or read book Data Science: From Research to Application written by Mahdi Bohlouli and published by Springer Nature. This book was released on 2020-01-28 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents outstanding theoretical and practical findings in data science and associated interdisciplinary areas. Its main goal is to explore how data science research can revolutionize society and industries in a positive way, drawing on pure research to do so. The topics covered range from pure data science to fake news detection, as well as Internet of Things in the context of Industry 4.0. Data science is a rapidly growing field and, as a profession, incorporates a wide variety of areas, from statistics, mathematics and machine learning, to applied big data analytics. According to Forbes magazine, “Data Science” was listed as LinkedIn’s fastest-growing job in 2017. This book presents selected papers from the International Conference on Contemporary Issues in Data Science (CiDaS 2019), a professional data science event that provided a real workshop (not “listen-shop”) where scientists and scholars had the chance to share ideas, form new collaborations, and brainstorm on major challenges; and where industry experts could catch up on emerging solutions to help solve their concrete data science problems. Given its scope, the book will benefit not only data scientists and scientists from other domains, but also industry experts, policymakers and politicians.

The Psychology of Fake News

Author : Rainer Greifeneder
Publisher : Routledge
ISBN 13 : 1000179052
Total Pages : 222 pages
Book Rating : 4.0/5 (1 download)

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Book Synopsis The Psychology of Fake News by : Rainer Greifeneder

Download or read book The Psychology of Fake News written by Rainer Greifeneder and published by Routledge. This book was released on 2020-08-13 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Detecting Fake News on Social Media

Author : Kai Shu
Publisher : Morgan & Claypool Publishers
ISBN 13 : 1681735830
Total Pages : 131 pages
Book Rating : 4.6/5 (817 download)

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Book Synopsis Detecting Fake News on Social Media by : Kai Shu

Download or read book Detecting Fake News on Social Media written by Kai Shu and published by Morgan & Claypool Publishers. This book was released on 2019-07-03 with total page 131 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Combating Fake News with Computational Intelligence Techniques

Author : Mohamed Lahby
Publisher : Springer Nature
ISBN 13 : 3030900878
Total Pages : 432 pages
Book Rating : 4.0/5 (39 download)

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Book Synopsis Combating Fake News with Computational Intelligence Techniques by : Mohamed Lahby

Download or read book Combating Fake News with Computational Intelligence Techniques written by Mohamed Lahby and published by Springer Nature. This book was released on 2021-12-15 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Graph Mining

Author : Deepayan Chakrabarti
Publisher : Morgan & Claypool Publishers
ISBN 13 : 160845116X
Total Pages : 209 pages
Book Rating : 4.6/5 (84 download)

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Book Synopsis Graph Mining by : Deepayan Chakrabarti

Download or read book Graph Mining written by Deepayan Chakrabarti and published by Morgan & Claypool Publishers. This book was released on 2012-10-01 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: What does the Web look like? How can we find patterns, communities, outliers, in a social network? Which are the most central nodes in a network? These are the questions that motivate this work. Networks and graphs appear in many diverse settings, for example in social networks, computer-communication networks (intrusion detection, traffic management), protein-protein interaction networks in biology, document-text bipartite graphs in text retrieval, person-account graphs in financial fraud detection, and others. In this work, first we list several surprising patterns that real graphs tend to follow. Then we give a detailed list of generators that try to mirror these patterns. Generators are important, because they can help with "what if" scenarios, extrapolations, and anonymization. Then we provide a list of powerful tools for graph analysis, and specifically spectral methods (Singular Value Decomposition (SVD)), tensors, and case studies like the famous "pageRank" algorithm and the "HITS" algorithm for ranking web search results. Finally, we conclude with a survey of tools and observations from related fields like sociology, which provide complementary viewpoints. Table of Contents: Introduction / Patterns in Static Graphs / Patterns in Evolving Graphs / Patterns in Weighted Graphs / Discussion: The Structure of Specific Graphs / Discussion: Power Laws and Deviations / Summary of Patterns / Graph Generators / Preferential Attachment and Variants / Incorporating Geographical Information / The RMat / Graph Generation by Kronecker Multiplication / Summary and Practitioner's Guide / SVD, Random Walks, and Tensors / Tensors / Community Detection / Influence/Virus Propagation and Immunization / Case Studies / Social Networks / Other Related Work / Conclusions

Deep Learning Techniques and Optimization Strategies in Big Data Analytics

Author : Thomas, J. Joshua
Publisher : IGI Global
ISBN 13 : 1799811948
Total Pages : 355 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Deep Learning Techniques and Optimization Strategies in Big Data Analytics by : Thomas, J. Joshua

Download or read book Deep Learning Techniques and Optimization Strategies in Big Data Analytics written by Thomas, J. Joshua and published by IGI Global. This book was released on 2019-11-29 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Fake Science

Author : Austin Ruse
Publisher : Simon and Schuster
ISBN 13 : 1621576140
Total Pages : 211 pages
Book Rating : 4.6/5 (215 download)

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Book Synopsis Fake Science by : Austin Ruse

Download or read book Fake Science written by Austin Ruse and published by Simon and Schuster. This book was released on 2017-07-17 with total page 211 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you listen to any political argument, you're eventually bound to hear something like: "The science is settled on this." Or: "Just look at the statistics!" Or: "There have been studies that say..." You'd think we were living in the golden age of science and reason. But the truth is far more sinister, says Austin Ruse. We're actually living in the age of the low information voter, easily mislead by all-too-convincing false statistics and studies. In Fake Science, Ruse debunks so-called "facts" used to advance political causes one after the other, revealing how poorly they stand up to actual science.

Confluence of AI, Machine, and Deep Learning in Cyber Forensics

Author : Misra, Sanjay
Publisher : IGI Global
ISBN 13 : 1799849015
Total Pages : 248 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Confluence of AI, Machine, and Deep Learning in Cyber Forensics by : Misra, Sanjay

Download or read book Confluence of AI, Machine, and Deep Learning in Cyber Forensics written by Misra, Sanjay and published by IGI Global. This book was released on 2020-12-18 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: Developing a knowledge model helps to formalize the difficult task of analyzing crime incidents in addition to preserving and presenting the digital evidence for legal processing. The use of data analytics techniques to collect evidence assists forensic investigators in following the standard set of forensic procedures, techniques, and methods used for evidence collection and extraction. Varieties of data sources and information can be uniquely identified, physically isolated from the crime scene, protected, stored, and transmitted for investigation using AI techniques. With such large volumes of forensic data being processed, different deep learning techniques may be employed. Confluence of AI, Machine, and Deep Learning in Cyber Forensics contains cutting-edge research on the latest AI techniques being used to design and build solutions that address prevailing issues in cyber forensics and that will support efficient and effective investigations. This book seeks to understand the value of the deep learning algorithm to handle evidence data as well as the usage of neural networks to analyze investigation data. Other themes that are explored include machine learning algorithms that allow machines to interact with the evidence, deep learning algorithms that can handle evidence acquisition and preservation, and techniques in both fields that allow for the analysis of huge amounts of data collected during a forensic investigation. This book is ideally intended for forensics experts, forensic investigators, cyber forensic practitioners, researchers, academicians, and students interested in cyber forensics, computer science and engineering, information technology, and electronics and communication.

Journalism, fake news & disinformation

Author : Ireton, Cherilyn
Publisher : UNESCO Publishing
ISBN 13 : 9231002813
Total Pages : 128 pages
Book Rating : 4.2/5 (31 download)

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Book Synopsis Journalism, fake news & disinformation by : Ireton, Cherilyn

Download or read book Journalism, fake news & disinformation written by Ireton, Cherilyn and published by UNESCO Publishing. This book was released on 2018-09-17 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Handbook of Research on Deception, Fake News, and Misinformation Online

Author : Chiluwa, Innocent E.
Publisher : IGI Global
ISBN 13 : 1522585370
Total Pages : 677 pages
Book Rating : 4.5/5 (225 download)

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Book Synopsis Handbook of Research on Deception, Fake News, and Misinformation Online by : Chiluwa, Innocent E.

Download or read book Handbook of Research on Deception, Fake News, and Misinformation Online written by Chiluwa, Innocent E. and published by IGI Global. This book was released on 2019-06-28 with total page 677 pages. Available in PDF, EPUB and Kindle. Book excerpt: The growing amount of false and misleading information on the internet has generated new concerns and quests for research regarding the study of deception and deception detection. Innovative methods that involve catching these fraudulent scams are constantly being perfected, but more material addressing these concerns is needed. The Handbook of Research on Deception, Fake News, and Misinformation Online provides broad perspectives, practices, and case studies on online deception. It also offers deception-detection methods on how to address the challenges of the various aspects of deceptive online communication and cyber fraud. While highlighting topics such as behavior analysis, cyber terrorism, and network security, this publication explores various aspects of deceptive behavior and deceptive communication on social media, as well as new methods examining the concepts of fake news and misinformation, character assassination, and political deception. This book is ideally designed for academicians, students, researchers, media specialists, and professionals involved in media and communications, cyber security, psychology, forensic linguistics, and information technology.

Disinformation, Misinformation, and Fake News in Social Media

Author : Kai Shu
Publisher : Springer Nature
ISBN 13 : 3030426998
Total Pages : 285 pages
Book Rating : 4.0/5 (34 download)

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Book Synopsis Disinformation, Misinformation, and Fake News in Social Media by : Kai Shu

Download or read book Disinformation, Misinformation, and Fake News in Social Media written by Kai Shu and published by Springer Nature. This book was released on 2020-06-17 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

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

Author : Management Association, Information Resources
Publisher : IGI Global
ISBN 13 : 1799872920
Total Pages : 653 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Research Anthology on Fake News, Political Warfare, and Combatting the Spread of Misinformation by : Management Association, Information Resources

Download or read book Research Anthology on Fake News, Political Warfare, and Combatting the Spread of Misinformation written by Management Association, Information Resources and published by IGI Global. This book was released on 2020-10-30 with total page 653 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Data Feminism

Author : Catherine D'Ignazio
Publisher : MIT Press
ISBN 13 : 0262358530
Total Pages : 328 pages
Book Rating : 4.2/5 (623 download)

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Book Synopsis Data Feminism by : Catherine D'Ignazio

Download or read book Data Feminism written by Catherine D'Ignazio and published by MIT Press. This book was released on 2020-03-31 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: A new way of thinking about data science and data ethics that is informed by the ideas of intersectional feminism. Today, data science is a form of power. It has been used to expose injustice, improve health outcomes, and topple governments. But it has also been used to discriminate, police, and surveil. This potential for good, on the one hand, and harm, on the other, makes it essential to ask: Data science by whom? Data science for whom? Data science with whose interests in mind? The narratives around big data and data science are overwhelmingly white, male, and techno-heroic. In Data Feminism, Catherine D'Ignazio and Lauren Klein present a new way of thinking about data science and data ethics—one that is informed by intersectional feminist thought. Illustrating data feminism in action, D'Ignazio and Klein show how challenges to the male/female binary can help challenge other hierarchical (and empirically wrong) classification systems. They explain how, for example, an understanding of emotion can expand our ideas about effective data visualization, and how the concept of invisible labor can expose the significant human efforts required by our automated systems. And they show why the data never, ever “speak for themselves.” Data Feminism offers strategies for data scientists seeking to learn how feminism can help them work toward justice, and for feminists who want to focus their efforts on the growing field of data science. But Data Feminism is about much more than gender. It is about power, about who has it and who doesn't, and about how those differentials of power can be challenged and changed.

How Algorithms Create and Prevent Fake News

Author : Noah Giansiracusa
Publisher :
ISBN 13 : 9781484271568
Total Pages : 0 pages
Book Rating : 4.2/5 (715 download)

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Book Synopsis How Algorithms Create and Prevent Fake News by : Noah Giansiracusa

Download or read book How Algorithms Create and Prevent Fake News written by Noah Giansiracusa and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: From deepfakes to GPT-3, deep learning is now powering a new assault on our ability to tell what's real and what's not, bringing a whole new algorithmic side to fake news. On the other hand, remarkable methods are being developed to help automate fact-checking and the detection of fake news and doctored media. Success in the modern business world requires you to understand these algorithmic currents, and to recognize the strengths, limits, and impacts of deep learning--especially when it comes to discerning the truth and differentiating fact from fiction. This book tells the stories of this algorithmic battle for the truth and how it impacts individuals and society at large. In doing so, it weaves together the human stories and what's at stake here, a simplified technical background on how these algorithms work, and an accessible survey of the research literature exploring these various topics. How Algorithms Create and Prevent Fake News is an accessible, broad account of the various ways that data-driven algorithms have been distorting reality and rendering the truth harder to grasp. From news aggregators to Google searches to YouTube recommendations to Facebook news feeds, the way we obtain information today is filtered through the lens of tech giant algorithms. The way data is collected, labelled, and stored has a big impact on the machine learning algorithms that are trained on it, and this is a main source of algorithmic bias - which gets amplified in harmful data feedback loops. Don't be afraid: with this book you'll see the remedies and technical solutions that are being applied to oppose these harmful trends. There is hope. .