True, justified, belief? Partisanship weakens the positive effect of news media literacy on fake news detection

To investigate how people assess whether politically consistent news is real or fake, two studies (N = 1,008; N = 1,397) with adult American participants conducted in 2020 and 2022 utilized a within-subjects experimental design to investigate perceptions of news accuracy. When a mock Facebook post with either fake (Study 1) or real (Study 2) news content was attributed to an alternative (vs. a mainstream) news outlet, it was, on average, perceived to be less accurate. Those with beliefs reflecting News Media Literacy demonstrated greater sensitivity to the outlet's status. This relationship was itself contingent on the strength of the participant's partisan identity. Strong partisans high in News Media Literacy defended the accuracy of politically consistent content, even while recognizing that an outlet was unfamiliar. These results highlight the fundamental importance of looking at the interaction between user-traits and features of social media news posts when examining learning from political news on social media.

Understanding news engagement on social media: A media repertoire approach

This study promotes the news repertoire framework as an analytical approach best suited for studying news engagement on social media (SM), considering its multifaceted nature. To demonstrate the theoretical benefits of this proposal, the study seeks to (1) identify user profiles based on SM news viewing and sharing, and news consumption on other platforms; (2) determine profile predictors; and (3) evaluate their possible outcomes. A panel study (N = 1786) demonstrated the emergence of identifiable profiles, attributed to differences in SM use and political interest. In addition, profiles embodied different effects on political participation over time. A second study (N = 86) was conducted thereafter, in which users' Facebook news feed use was analyzed to determine differences in news supply according to profiles. Findings that could not have been achieved using the more common unidimensional news consumption methods are discussed in light of new theoretical gains provided by the repertoire approach.

"You're still worth it": The moral and relational context of politically motivated unfriending decisions in online networks

Political disagreements in social media can result in removing (i.e., “unfriending”) a person from one’s online network. Given that such actions could lead to the (ideological) homogenization of networks, it is pivotal to understand the psychological processes intertwined in unfriending decisions. This requires not only addressing different types of disagreements but also analyzing them in the relational context they occur. This article proposes that political disagreements leading to drastic measures such as unfriending are attributable to more deeply rooted moral dissents. Based on moral foundations theory and relationship regulation research, this work presents empirical evidence from two experiments. In both studies, subjects rated political statements (that violated different moral foundations) with regard to perceived reprehensibility and the likelihood of unfriending the source. Study 1 (N = 721) revealed that moral judgments of a political statement are moderately related to the unfriending decision. Study 2 (N = 822) replicated this finding but indicated that unfriending is less likely when the source of the morally reprehensible statement is relationally close to the unfriender and provides emotional support. This research extends unfriending literature by pointing to morality as a new dimension of analysis and offers initial evidence uncovering the psychological trade-off behind the decision of terminating digital ties. Drawing on this, our findings inform research on the homogenization of online networks by indicating that selective avoidance (in the form of politically motivated unfriending) is conditional upon the relational context and the interpersonal benefits individuals receive therein.