The proliferation of misinformation in online news and its amplification by platforms are a growing concern, leading to numerous efforts to improve the detection of and response to misinformation. Given the variety of approaches, collective agreement on the indicators that signify credible content could allow for greater collaboration and data-sharing across initiatives. In this paper, we present an initial set of indicators for article credibility defined by a diverse coalition of experts. These indicators originate from both within an article's text as well as from external sources or article metadata. As a proof-of-concept, we present a dataset of 40 articles of varying credibility annotated with our indicators by 6 trained annotators using specialized platforms. We discuss future steps including expanding annotation, broadening the set of indicators, and considering their use by platforms and the public, towards the development of interoperable standards for content credibility.This paper is published under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. Authors reserve their rights to disseminate the work on their personal and corporate Web sites with the appropriate attribution.

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How do the reasons people post misinformation affect how they respond to fact checking interventions? In this research, we conducted a qualitative study of people who shared misinformation. We started with stories marked as false by a popular fact checker, Snopes, and identified people who posted those stories on Reddit. We interviewed the posters about the story they shared and their five behaviorally distinct personas: Reason to Disagree, Changed Belief, Steadfast Non-Standard Belief, Sharing to Debunk, and Sharing for Humor. Our findings suggest that research to craft better interventions to counter misinformation might benefit from tailoring to specific personas that can serve as design tools for on-going misinformation intervention research.