## 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 language | English (US) |
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Title of host publication | 2023 IEEE International Symposium on Information Theory, ISIT 2023 |

Publisher | Institute of Electrical and Electronics Engineers Inc. |

Pages | 2649-2654 |

Number of pages | 6 |

ISBN (Electronic) | 9781665475549 |

DOIs | |

State | Published - 2023 |

Event | 2023 IEEE International Symposium on Information Theory, ISIT 2023 - Taipei, Taiwan, Province of China Duration: Jun 25 2023 → Jun 30 2023 |

### Publication series

Name | IEEE International Symposium on Information Theory - Proceedings |
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Volume | 2023-June |

ISSN (Print) | 2157-8095 |

### Conference

Conference | 2023 IEEE International Symposium on Information Theory, ISIT 2023 |
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Country/Territory | Taiwan, Province of China |

City | Taipei |

Period | 6/25/23 → 6/30/23 |

### Bibliographical note

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