Fake news detection: a survey of evaluation datasets.

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From: PeerJ Computer Science(Vol. 7)
Publisher: PeerJ. Ltd.
Document Type: Article
Length: 10,737 words
Lexile Measure: 1490L

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Abstract :

Fake news detection has gained increasing importance among the research community due to the widespread diffusion of fake news through media platforms. Many dataset have been released in the last few years, aiming to assess the performance of fake news detection methods. In this survey, we systematically review twenty-seven popular datasets for fake news detection by providing insights into the characteristics of each dataset and comparative analysis among them. A fake news detection datasets characterization composed of eleven characteristics extracted from the surveyed datasets is provided, along with a set of requirements for comparing and building new datasets. Due to the ongoing interest in this research topic, the results of the analysis are valuable to many researchers to guide the selection or definition of suitable datasets for evaluating their fake news detection methods.

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Gale Document Number: GALE|A665558210