Can online attention signals help fact-checkers fact-check?
Manoel Horta Ribeiro, Savvas Zannettou, Oana Goga, Fabr\'icio, Benevenuto, Robert West

TL;DR
This paper introduces a framework that leverages online attention signals to analyze and potentially enhance fact-checking efforts, especially in the context of COVID-19 misinformation, by linking claims to online attention data.
Contribution
It proposes a novel framework combining claim extraction, knowledge graph linking, and attention estimation to study fact-checking dynamics using online attention signals.
Findings
Many claims are not fact-checked despite high online attention.
Fact-checking often occurs after a significant portion of attention is received.
Online attention signals can inform better timing and focus of fact-checking efforts.
Abstract
Recent research suggests that not all fact-checking efforts are equal: when and what is fact-checked plays a pivotal role in effectively correcting misconceptions. In that context, signals capturing how much attention specific topics receive on the Internet have the potential to study (and possibly support) fact-checking efforts. This paper proposes a framework to study fact-checking with online attention signals. The framework consists of: 1) extracting claims from fact-checking efforts; 2) linking such claims with knowledge graph entities; and 3) estimating the online attention these entities receive. We use this framework to conduct a preliminary study of a dataset of 879 COVID-19-related fact-checks done in 2020 by 81 international organizations. Our findings suggest that there is often a disconnect between online attention and fact-checking efforts. For example, in around 40% of…
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Taxonomy
TopicsMisinformation and Its Impacts · Computational and Text Analysis Methods · Public Relations and Crisis Communication
