Finding, Monitoring, and Checking Claims Computationally Based on Structured Data

Part of: Computation+Journalism Symposium 2014

Authors

    • Duke University
    • Brett Walenz
    • You (Will) Wu
    • Seokhyun Alex Song
    • Emre Sonmez
    • Eric Wu
    • Kevin Wu
    • Pankaj K Agarwal
    • Jun Yang
    • University of Texas at Arlington
    • Naeemul Hassan
    • Afroza Sultana
    • Gensheng Zhang
    • Chengkai Li
    • Cong Yu
    • Google Research
    • Cong Yu

Abstract

"Big data" have arrived. The increasing abundance of data brings many opportunities for journalism, from discovering interesting stories to fact-checking claims. Unfortunately, the skill of making sense out of data is in short supply; software tools suitable for nontechnical users are sorely lacking. The gap between the abundance of data and the shortage of human expertise seems to be widening. Unless we find a way to close this gap, big data will not achieve its potential for journalism. Moreover, the public may become more susceptible to “lies, d—ed lies, and statistics” that nitpick data to advance their own arguments. We present our work on the use of data in finding stories and checking facts, as well as the associated challenges.