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

A general framework to link theory and empirics in opinion formation models

We introduce a minimal opinion formation model that is quite flexible and can reproduce a wide variety of the existing micro-influence assumptions and models. The model can be easily calibrated on real data, upon which it imposes only a few requirements. From this perspective, our model can be considered as a bridge, connecting theoretical studies on opinion formation models and empirical research on social dynamics. We investigate the model analytically by using mean-field approximation and numerically via Monte Carlo simulations. Our analysis is exemplified by recently reported empirical data drawn from an online social network. We demonstrate that the model calibrated on these data may reproduce fragmented and polarizing social systems. Furthermore, we manage to generate an artificial society that features properties quantitatively and qualitatively similar to those observed empirically at the macro scale. This ability became possible after we had advanced the model with two important communication features: selectivity and personalization algorithms.

When You Are Wrong on Facebook, Just Admit It

Abstract. Intellectually humble behavior, like admitting when you are wrong, leads to better impression formation. However, online social networks (OSNs) have changed the impression formation process. We investigated the impact of wrongness admission on impression formation during an OSN argument. In four experiments ( N = 679), participants witnessed a user engage in wrongness admission, refuse to admit, or not respond, in an argument on a Facebook wall. Participants reported their impressions of whether they would be willing to interact with the (non)admitting user. User reputation ratings and interaction intentions were higher in the admission (vs. nonadmission) condition. The latter effect was mediated by user reputation ratings. Wrongness admission appears to have a positive impact on impression formation on OSNs.

Out-of-Place Content: How Repetitive, Offensive, and Opinion-Challenging Social Media Posts Shape Users’ Unfriending Strategies in Spain

Filtering strategies enable social media users to remove undesired content from their feeds, potentially creating homophilic environments. Although previous studies have addressed the individual-level factors and content features that influence these decisions, few have solely focused on users’ perceptions. Accordingly, this study applies social exchange theory to understand how users socially construct the process of unfriending. Based on 30 in-depth interviews with young Spaniards, we identify a widespread pattern of rejection over repetitive, opinion-challenging, and offensive posts, which we conceptualize as out-of-place content, a type of social media stimulus that hinders substantive online exchanges and challenges users’ understanding of social reality and individual values. This study contributes to current literature on unfriending by suggesting that filtering strategies are implemented gradually when posts overwhelm users’ tolerance threshold. Our findings also suggest that their deployment hinges on the closeness of the relationship between peers and social commitments formed in specific platforms. Future research is needed to assess to what extent the patterns identified in our interviews are present in the overall population.