Fake news is counterfeit news

Fallis, Don; Mathiesen, Kay

doi:10.1080/0020174x.2019.1688179

Cited by 51 publications

(36 citation statements)

References 11 publications

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“…In many countries, misinformation grounded in complete disregard for evidence has created grounds to fake information to spread further cementing resistance among some individuals [16] . One can argue that the misinformation era and disregard for facts/evidence in which we have entered is typified by public figures, political and officials noting "fake news” to dismiss factual information, “truth isn't truth” and "alternative facts" [ 21 , 16 ]. No longer is misinformation only generated and distributed by people at the bottom of organizational hierarchies, but at all levels of organizations.…”

Section: Resultsmentioning

confidence: 99%

COVID-19 and counterfeit vaccines: Global implications, new challenges and opportunities

Amankwah‐Amoah

2022

Health Policy and Technology

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Section: Resultsmentioning

confidence: 99%

COVID-19 and counterfeit vaccines: Global implications, new challenges and opportunities

Amankwah‐Amoah

2022

Health Policy and Technology

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“…One definition makes the distinction between fake and genuine news. Fake news is counterfeit news, while genuine news is comprised of news that has gone through fact checkers and editors [6]. Another definition of fake news refers to news articles that contain verifiably false information intentionally created to mislead others [7].…”

Section: Fake News and Social Mediamentioning

confidence: 99%

Social Media and Fake News Detection using Adversarial Collaboration

D’Souza¹,

French²

2022

Proceedings of the Annual Hawaii International Conference on System Sciences

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The diffusion of fake information on social media networks obscures public perception of events, news, and relevant content. Intentional misleading news may promote negative online experiences and influence societal behavioral changes such as increased anxiety, loneliness, and inadequacy. Adversarial attacks target creating misinformation in online information systems. This behavior can be viewed as an instrument to manipulate the online social media networks for cultural, social, economic, and political gains. A method to test a deep learning model-long short-term memory (LSTM) using adversarial examples generated from a transformer model has been presented. The paper attempts to examine features in machine learning algorithms that propagate fake news. Another goal is to evaluate and compare the usefulness of generative adversarial networks with long-term short-term recurrent neural network algorithms in identifying fake news. A closer look at the mechanisms of implementing adversarial attacks in social media systems helps build robust intelligent systems that can withstand future vulnerabilities.

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“…That is, a purveyor of disinformation can deceive an audience about the veracity of a news item as well as deceiving an audience about their own status as a journalist. They can, for example, present content as though it were the product of genuine journalistic practices when, in fact, it was not (Fallis and Mathiesen 2019;Pepp et al 2019). Finally, misleading content is characterized by the effect that it has on the audience.…”

Section: The Policy Challenge: What Content Should Moderation Target?mentioning

confidence: 99%

Detecting Fake News: Two Problems for Content Moderation

Stewart

2021

Philos. Technol.

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The spread of fake news online has far reaching implications for the lives of people offline. There is increasing pressure for content sharing platforms to intervene and mitigate the spread of fake news, but intervention spawns accusations of biased censorship. The tension between fair moderation and censorship highlights two related problems that arise in flagging online content as fake or legitimate: firstly, what kind of content counts as a problem such that it should be flagged, and secondly, is it practically and theoretically possible to gather and label instances of such content in an unbiased manner? In this paper, I argue that answering either question involves making value judgements that can generate user distrust toward fact checking efforts.

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Fake news is counterfeit news

Cited by 51 publications

References 11 publications

COVID-19 and counterfeit vaccines: Global implications, new challenges and opportunities

COVID-19 and counterfeit vaccines: Global implications, new challenges and opportunities

Social Media and Fake News Detection using Adversarial Collaboration

Detecting Fake News: Two Problems for Content Moderation

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