ICheck: Computationally combating "lies, D - Ned Lies, and statistics"

Published

Journal Article

Are you fed up with "lies, d - ned lies, and statistics" made up from data in our media? For claims based on structured data, we present a system to automatically assess the quality of claims (beyond their correctness) and counter misleading claims that cherry-pick data to advance their conclusions. The key insight is to model such claims as parameterized queries and consider how parameter perturbations affect their results. We demonstrate our system on claims drawn from U.S. congressional voting records, sports statistics, and publication records of database researchers.

Full Text

Duke Authors

Cited Authors

  • Wu, Y; Walenz, B; Li, P; Shim, A; Sonmez, E; Agarwal, PK; Li, C; Yang, J; Yu, C

Published Date

  • January 1, 2014

Published In

Start / End Page

  • 1063 - 1066

International Standard Serial Number (ISSN)

  • 0730-8078

Digital Object Identifier (DOI)

  • 10.1145/2588555.2594522

Citation Source

  • Scopus