Abstract
When users on social media share content without considering its veracity, they may unwittingly be spreading misinformation. In this work, we investigate the design of lightweight interventions that nudge users to assess the accuracy of information as they share it. Such assessment may deter users from posting misinformation in the first place, and their assessments may also provide useful guidance to friends aiming to assess those posts themselves. In support of lightweight assessment, we first develop a taxonomy of the reasons why people believe a news claim is or is not true; this taxonomy yields a checklist that can be used at posting time. We conduct evaluations to demonstrate that the checklist is an accurate and comprehensive encapsulation of people's free-response rationales. In a second experiment, we study the effects of three behavioral nudges---1) checkboxes indicating whether headings are accurate, 2) tagging reasons (from our taxonomy) that a post is accurate via a checklist and 3) providing free-text rationales for why a headline is or is not accurate---on people's intention of sharing the headline on social media. From an experiment with 1668 participants, we find that both providing accuracy assessment and rationale reduce the sharing of false content. They also reduce the sharing of true content, but to a lesser degree that yields an overall decrease in the fraction of shared content that is false. Our findings have implications for designing social media and news sharing platforms that draw from richer signals of content credibility contributed by users. In addition, our validated taxonomy can be used by platforms and researchers as a way to gather rationales in an easier fashion than free-response.
Highlights
Social media has lowered the barrier to publishing content
We study the effects of three behavioral nudges—1) checkboxes indicating whether headings are accurate, 2) tagging reasons that a post is accurate via a checklist and 3) providing free-text rationales for why a headline is or is not accurate—on people’s intention of sharing the headline on social media
We developed a taxonomy of reasons and presented a set of claims along with the taxonomy to participants to choose from, as they provided their rationales for theaccuracy of the news claims
Summary
Social media has lowered the barrier to publishing content. While this empowerment of the individual has led to positive outcomes, it has encouraged the fabrication of misinformation by malicious actors and its circulation by unwitting platform users [24, 75]. Given widespread concerns about misinformation on social media [6, 8, 15, 18, 60], many researchers have investigated measures to counter misinformation on these platforms Some of these initiatives include detecting false or misleading information using machine learning algorithms [12, 57, 67] and crowdsourcing [5, 9, 19, 33, 54], identifying bad actors and helping good actors differentiate themselves1 [82], and providing fact-checked information related to circulated news claims [23, 35, 50, 81]. A related driver is an emphasis on low barriers to sharing that allows users to share content without much attention to its accuracy or potential negative consequences, to receive social feedback or elevated engagement [7, 25]
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