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Many social-media websites struggle to maximize user engagement while minimizing the amount of misinformation shared and reshared. The stakes are high for Facebook, Twitter, and their rivals, which generate most of their revenue from advertising. Viral content leads to higher user engagement, which in turn leads to more advertising revenue. But content-management algorithms designed to maximize user engagement may inadvertently promote content of dubious quality-including fake news. Recommended Reading There's reason to doubt fake news handed Trump the election. CBR - Economics Candogan and Drakopoulos use modeling to test strategies for striking a balance between these conflicting goals. Their findings suggest that spreading misinformation poses a business risk for social-media platforms, as users might come to believe they can't trust the information they see. The researchers' models assume platform operators can tell the difference between factual and fictitious posts. They demonstrate that engagement levels fall when users aren't warned of posts that contain misinformation-to levels lower than when users are discouraged from clicking on the dubious material. In the researchers' models, clicks fell by more than half when platforms had a "no-intervention" policy. But while the models initially assumed that users were relatively indifferent to misinformation, when users were in fact concerned about engaging with erroneous content, failing to intervene led to an even greater drop in engagement, with the number of clicks dwindling to zero. The research also explored a sample of 4,039 de-identified Facebook users, created as part of a larger network analysis project at Stanford. The Stanford team collected information, including connections, from volunteer Facebook users. A limitation of the research is the models' assumption that the people using social networks and the algorithms running them know whether posts are true, false, or shaded somewhere in between. "This assumption is an approximation to reality, where a platform potentially has a more accurate estimate of the error than the agents," Candogan and Drakopoulos write. high quality imitation bagsimitation bags

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