FactCatch: Incremental Pay-as-You-Go Fact Checking with Minimal User Effort
The open nature of the Web enables users to produce and propagate any content without authentication, which has been exploited to spread thousands of unverified claims via millions of online documents. Maintenance of credible knowledge bases thus has to rely on fact checking that constructs a trusted set of facts through credibility assessment. Due to an inherent lack of ground truth information and language ambiguity, fact checking cannot be done in a purely automated manner without compromising accuracy. However, state-of-the-art fact checking services, rely mostly on human validation, which is costly, slow, and non-transparent. This paper presents FactCatch, a human-in-the-loop system to guide users in fact checking that aims at minimisation of the invested effort. It supports incremental quality estimation, mistake mitigation, and pay-as-you-go instantiation of a high-quality fact database.
WOS:000722377700322
2020-01-01
978-1-4503-8016-4
New York
2165
2168
REVIEWED
Event name | Event place | Event date |
ELECTR NETWORK | Jul 25-30, 2020 | |