tutorial

Fake News Propagation: A Review of Epidemic Models, Datasets, and Insights

Authors:

Zeinab Khalifa,

Gabriele Oligeri,

Roberto Di PietroAuthors Info & Claims

ACM Transactions on the Web (TWEB), Volume 16, Issue 3

Article No.: 12, Pages 1 - 34

https://doi.org/10.1145/3522756

Published: 19 September 2022 Publication History

Abstract

Fake news propagation is a complex phenomenon influenced by a multitude of factors whose identification and impact assessment is challenging. Although many models have been proposed in the literature, the one capturing all the properties of a real fake-news propagation phenomenon is inevitably still missing. Modern propagation models, mainly inspired by old epidemiological models, attempt to approximate the fake-news propagation phenomena by blending psychological factors, social relations, and user behavior.

This work provides an in-depth analysis of the current state of fake-news propagation models supported by real-world datasets. We highlighted similarities and differences in the modeling approaches, wrapping up the main research trends. Propagation models, transitions, network topologies, and performance metrics have been identified and discussed in detail. The thorough analysis we provided in this article, coupled with the highlighted research hints, have a high potential to pave the way for future research in the area.

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cover image ACM Transactions on the Web

ACM Transactions on the Web Volume 16, Issue 3

August 2022

155 pages

ISSN:1559-1131

EISSN:1559-114X

DOI:10.1145/3555790

Editor:
Ryen White
Microsoft Research, USA

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Publication History

Published: 19 September 2022

Online AM: 30 March 2022

Accepted: 27 February 2022

Revised: 08 December 2021

Received: 23 May 2021

Published in TWEB Volume 16, Issue 3

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