Characterizing Fake News: A Conceptual Modeling-based Approach

Belloir, Nicolas; Ouerdane, Wassila; Pastor, Oscar

doi:10.1007/978-3-031-17995-2_9

Cited by 6 publications

(3 citation statements)

References 21 publications

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“…This was accomplished by proposing conceptual meta-models that provide general clarification and guidance on the understanding of the said domain. For instance, we report recent work in the context of fake news [51,6], Virtual Network Function Marketplaces [20], FAIR scientific datasets [8], or FAIR Digital Objects [47].…”

Section: Related Workmentioning

confidence: 99%

A Reference Meta-model to Understand DNA Variant Interpretation Guidelines

Costa,

S.,

Leon

et al. 2023

Lecture Notes in Computer Science

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Determining the role of a DNA variant in patients' health status -a process known as variant interpretation -is highly critical for precision medicine applications. Variant interpretation involves a complex process where, regrettably, there is still debate on how to combine and weigh diverse available evidence to achieve proper and consistent answers. Indeed, at the time of writing, 22 different variant interpretation guidelines are available to the scientific community, each of them attempting to establish a framework for standardizing the interpretation process. However, these guidelines are qualitative and vague by nature, which hinders their streamlined application and potential automation. Consequently, more precise definitions are needed. Conceptual modeling provides the means to bring clarification within this domain. This paper presents our efforts to define and use a UML meta-model that describes the main concepts involved in the definition of variant interpretation guidelines and the constructs they evaluate. The precise conceptual definition of the guidelines allowed us to identify four common misinterpretation patterns that hamper the correct interpretation process and that can consequently affect classification results. In several proposed examples, the use of the meta-model provides support in identifying the inconsistencies in the observed process; this result paves the way for further proposing reconciliation strategies for the existing guidelines.

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Section: Related Workmentioning

confidence: 99%

A Reference Meta-model to Understand DNA Variant Interpretation Guidelines

Costa,

S.,

Leon

et al. 2023

Lecture Notes in Computer Science

Self Cite

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“…The data can also be used to study phenomena created through social networks, one of them being the growth and dissemination of misinformation [Belloir et al 2022, Rath et al 2020, Burbach et al 2019. Another phenomenon associated with OSNs (and their underlying algorithms) are filter bubbles [Matakos et al 2020].…”

Section: Introductionmentioning

confidence: 99%

Database Support for Online Social Network Analysis

Pintor,

Salgueiro,

Lifschitz

et al. 2023

Anais Do XXXVIII Simpósio Brasileiro De Banco De Dados (SBBD 2023)

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Online Social Networks (OSNs) have become part of our daily life, contributing to the vast amount of data generated online. The OSNs' data contribute to obtaining information about our society in various areas, such as misinformation, politics, marketing, and engagement metrics. OSN is a comparatively new concept, without a generic model, with problem-specific models used for the studies of it. This article demonstrates the use of logical models to analyze data from different OSNs, based on a generic conceptual model that reflects a general definition of social networks. These examples aim to show the feasibility and advantages of using the generic model as a basis for specific OSN models, to support the analyses performed from the data extracted.

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“…Studying the fake news literature, Belloir et al (2022) noticed that the concept of fake news is still ambiguous, and the frontier between the definition of fake news and other related concepts, such as misinformation, disinformation, hoax news, propaganda news, etc., is blurred. Also, it is not always clear or precise how these different concepts are related, or how we can distinguish between themes.…”

Section: Introductionmentioning

confidence: 99%

Psychological effects of fake news – literature review

Mihai¹

2022

JESP

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"Fake news is one of the most discussed topics in the last few years. During the COVID-19 pandemic and during the Ukrainian war, the dangerous nature of this phenomenon became more obvious. More politics and more journalists are using now (fake) news as a weapon. Modern war must be considered in its informational part also. So, a correct evaluation of the news is an important skill for their consumers. Which are the psychological effects of fake news on the audience? Which is the psychological profile of the people that consume fake news? Which people are more vulnerable to suffering its negative effects? Why do people believe and share fake information? How can we explain the failure to distinguish accurate from inaccurate news? We studied the recent research in order to find the answers. This study is a literature review on the argument of fake news, its psychological effects on people and some explanations for this phenomenon. "

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Characterizing Fake News: A Conceptual Modeling-based Approach

Cited by 6 publications

References 21 publications

A Reference Meta-model to Understand DNA Variant Interpretation Guidelines

A Reference Meta-model to Understand DNA Variant Interpretation Guidelines

Database Support for Online Social Network Analysis

Psychological effects of fake news – literature review

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