On the modeling and verification of the spread of fake news, algebraically.
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| Title: | On the modeling and verification of the spread of fake news, algebraically. |
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| Authors: | Aldini, Alessandro1 (AUTHOR) alessandro.aldini@uniurb.it |
| Source: | Journal of Logic & Computation. Sep2022, Vol. 32 Issue 6, p1272-1291. 20p. |
| Subjects: | Fake news, Probabilistic number theory, Online social networks, Modal logic, Social networks |
| Abstract: | In recent years, one of the major issues concerning the study of online social network phenomena is related to the diffusion of misinformation, commonly known as fake news. In the literature, several mathematical tools are used to investigate both the identifying attributes of fake news and their spreading model. This work concentrates on the latter aspect and follows the lines of research inspired by the analysis of epidemic models. Its main contribution is the definition of a modeling framework based on process algebra for the explicit, formal representation of typical behavioral patterns of agents in social networks, and the use of a probabilistic verification framework based on modal logics and model checking for the quantitative analysis of the fake news spread. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Logic & Computation is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Abstract: | In recent years, one of the major issues concerning the study of online social network phenomena is related to the diffusion of misinformation, commonly known as fake news. In the literature, several mathematical tools are used to investigate both the identifying attributes of fake news and their spreading model. This work concentrates on the latter aspect and follows the lines of research inspired by the analysis of epidemic models. Its main contribution is the definition of a modeling framework based on process algebra for the explicit, formal representation of typical behavioral patterns of agents in social networks, and the use of a probabilistic verification framework based on modal logics and model checking for the quantitative analysis of the fake news spread. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 0955792X |
| DOI: | 10.1093/logcom/exac015 |
