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Towards an axiomatic approach to truth discovery

Singleton, Joseph and Booth, Richard ORCID: 2022. Towards an axiomatic approach to truth discovery. Autonomous Agents and Multi-Agent Systems 36 , 42. 10.1007/s10458-022-09569-3

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The problem of truth discovery, i.e., of trying to find the true facts concerning a number of objects based on reports from various information sources of unknown trustworthiness, has received increased attention recently. The problem is made interesting by the fact that the relative believability of facts depends on the trustworthiness of their sources, which in turn depends on the believability of the facts the sources report. Several algorithms for truth discovery have been proposed, but their evaluation has mainly been performed experimentally by computing accuracy against large datasets. Furthermore, it is often unclear how these algorithms behave on an intuitive level. In this paper we take steps towards a framework for truth discovery which allows comparison and evaluation of algorithms based instead on their theoretical properties. To do so we pose truth discovery as a social choice problem, and formulate various axioms that any reasonable algorithm should satisfy. Along the way we provide an axiomatic characterisation of the baseline ‘Voting’ algorithm – which leads to an impossibility result showing that a certain combination of the axioms cannot hold simultaneously – and check which axioms a particular well-known algorithm satisfies. We find that, surprisingly, our more fundamental axioms do not hold, and propose modifications to the algorithms to partially fix these problems.

Item Type: Article
Date Type: Published Online
Status: Published
Schools: Computer Science & Informatics
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Additional Information: This article is licensed under a Creative Commons Attribution 4.0 International License
Publisher: Springer
ISSN: 1387-2532
Date of First Compliant Deposit: 21 June 2022
Date of Acceptance: 20 June 2022
Last Modified: 24 May 2023 00:03

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