Distributed Fact Checking

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We formulate the problem of fake news detection using distributed inexpert agents. We consider the source for news/statements as a binary source (to model true vs. false statements). Upon observing news, each agent labels the news as true or false, which equals the validity of the statement with some probability depending on the reliability of the agent. In other words, each agent is viewed as a Binary Symmetric Channel (BSC) that misclassifies each statement with some error probability. For an algorithm that estimates the validity by thresholding a linear combination of the individual agents' labels, we characterize the optimal weights and threshold to minimize the probability of error. We establish an upper bound on this probability of error as well as the naive majority rule.

Original languageEnglish (US)
Title of host publication2023 IEEE International Symposium on Information Theory, ISIT 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2649-2654
Number of pages6
ISBN (Electronic)9781665475549
DOIs
StatePublished - 2023
Event2023 IEEE International Symposium on Information Theory, ISIT 2023 - Taipei, Taiwan, Province of China
Duration: Jun 25 2023Jun 30 2023

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
Volume2023-June
ISSN (Print)2157-8095

Conference

Conference2023 IEEE International Symposium on Information Theory, ISIT 2023
Country/TerritoryTaiwan, Province of China
CityTaipei
Period6/25/236/30/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

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