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When users on social media share content without considering its veracity,they may unwittingly be spreading misinformation. In this work, we investigatethe design of lightweight interventions that nudge users to assess the accuracyof information as they share it. Such assessment may deter users from postingmisinformation in the first place, and their assessments may also provideuseful guidance to friends aiming to assess those posts themselves. In supportof lightweight assessment, we first develop a taxonomy of the reasons whypeople believe a news claim is or is not true; this taxonomy yields a checklistthat can be used at posting time. We conduct evaluations to demonstrate thatthe checklist is an accurate and comprehensive encapsulation of people'sfree-response rationales. In a second experiment, we study the effects of threebehavioral nudges -- 1) checkboxes indicating whether headings are accurate, 2)tagging reasons (from our taxonomy) that a post is accurate via a checklist and3) 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 anexperiment with 1668 participants, we find that both providing accuracyassessment and rationale reduce the sharing of false content. They also reducethe sharing of true content, but to a lesser degree that yields an overalldecrease in the fraction of shared content that is false. Our findings haveimplications for designing social media and news sharing platforms that drawfrom richer signals of content credibility contributed by users. In addition,our validated taxonomy can be used by platforms and researchers as a way togather rationales in an easier fashion than free-response.

Exploring Lightweight Interventions at Posting Time to Reduce the Sharing of Misinformation on Social Media