Struggling to curb misinformation, social media platforms are experimenting with design interventions to enhance consumption of credible news on their platforms. Some of these interventions, such as the use of warning messages, are examples of nudges---a choice-preserving technique to steer behavior. Despite their application, we do not know whether nudges could steer people into making conscious news credibility judgments online and if they do, under what constraints. To answer, we combine nudge techniques with heuristic based information processing to design NudgeCred--a browser extension for Twitter. NudgeCred directs users' attention to two design cues: authority of a source and other users' collective opinion on a report by activating three design nudges---Reliable, Questionable, and Unreliable, each denoting particular levels of credibility for news tweets. In a controlled experiment, we found that NudgeCred significantly helped users (n=430) distinguish news tweets' credibility, unrestricted by three behavioral confounds---political ideology, political cynicism, and media skepticism. A five-day field deployment with twelve participants revealed that NudgeCred improved their recognition of news items and attention towards all of our nudges, particularly towards Questionable. Among other considerations, participants proposed that designers should incorporate heuristics that users' would trust. Our work informs nudge-based system design approaches for online media.
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FeedReflect: A Tool for Nudging Users to Assess News Credibility on Twitter
In recent years, the emergence of fake news outlets has drawn out the importance of news literacy. This is particularly critical in social media where the flood of information makes it difficult for people to assess the veracity of the false stories from such deceitful sources. Therefore, people oftentimes fail to look skeptically at these stories. We explore a way to circumvent this problem by nudging users into making conscious assessments of what online contents are credible. For this purpose, we developed FeedReflect, a browser extension. The extension nudges users to pay more attention and uses reflective questions to engage in news credibility assessment on Twitter. We recruited a small number of university students to use this tool on Twitter. Both qualitative and quantitative analysis of the study suggests the extension helped people accurately assess the credibility of news. This implies FeedReflect can be used for the broader audience to improve online news literacy.
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- NSF-PAR ID:
- 10082960
- Date Published:
- Journal Name:
- CSCW '18 Companion of the 2018 ACM Conference on Computer Supported Cooperative Work and Social Computing
- Page Range / eLocation ID:
- 205 to 208
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3272973.3274056
