We studied the effects of exposure to reshared content on Facebook during the 2020 US election by assigning a random set of consenting, US-based users to feeds that did not contain any reshares over a 3-month period.
We investigated the effects of Facebook’s and Instagram’s feed algorithms during the 2020 US election. We assigned a sample of consenting users to reverse-chronologically-ordered feeds instead of the default algorithms. Moving users out of algorithmic feeds substantially decreased the time they spent on the platforms and their activity.
Does Facebook enable ideological segregation in political news consumption? We analyzed exposure to news during the US 2020 election using aggregated data for 208 million US Facebook users. We compared the inventory of all political news that users could have seen in their feeds with the information that they saw (after algorithmic curation) and the information with which they engaged.
The CDC's ability to respond to communicable disease threats has recently met significant political and legal opposition. We (a) unpack the influence of political ideology on support for CDC authority, and (b) experimentally assess whether highlighting its role in responding to health threats might bolster CDC support.
Throughout the COVID-19 pandemic, researchers have studied how Americans' attitudes toward health experts influence their health behaviors and policy opinions. Fewer, however, consider the potential gap between individual and expert opinion about COVID-19, and how that might shape health attitudes and behavior.