Social interactions play an extremely important role in maintaining health and well-being. The COVID-19 pandemic and associated physical distancing measures, however, restricted the number of people one could physically interact with on a regular basis. A large percentage of social interactions moved online, resulting in reports of “Zoom fatigue,” or exhaustion from virtual interactions. These reports focused on how online communication differs from in-person communication, but it is possible that when in-person interactions are restricted, virtual interactions may benefit mental health overall. In a survey conducted near the beginning of the COVID-19 pandemic (N2020 = 230), we found that having a greater number of virtual interaction partners was associated with better mental health. This relationship was statistically mediated by decreased loneliness and increased perceptions of social support. We replicated these findings during the pandemic 1 year later (N2021 = 256) and found that these effects held even after controlling for the amount of time people spent interacting online. Convergent with previous literature on social interactions, these findings suggest that virtual interactions may benefit overall mental health, particularly during physical distancing and other circumstances where opportunities to interact in-person with different people are limited.Open Science Framework repository: https://osf.io/6jsr2/.

Social interactions unfold within networks of relationships. How do beliefs about others’ social ties shape—and how are they shaped by—expectations about how others will behave? Here, participants joined a fictive online game-playing community and interacted with its purported members, who varied in terms of their trustworthiness and apparent relationships with one another. Participants were less trusting of partners with untrustworthy friends, even after they consistently showed themselves to be trustworthy, and were less willing to engage with them in the future. To test whether people not only expect friends to behave similarly but also expect those who behave similarly to be friends, an incidental memory test was given. Participants were exceptionally likely to falsely remember similarly behaving partners as friends. Thus, people expect friendship to predict similar behavior and vice versa. These results suggest that knowledge of social networks and others’ behavioral tendencies reciprocally interact to shape social thought and behavior.

Social interactions unfold within networks of relationships. How do beliefs about others’ social ties shape—and how are they shaped by—expectations about how others will behave? Here, participants joined a fictive online game-playing community and interacted with its purported members, who varied in terms of their trustworthiness and apparent relationships with one another. Participants were less trusting of partners with untrustworthy friends, even after they consistently showed themselves to be trustworthy, and were less willing to engage with them in the future. To test if people not only expect friends to behave similarly, but also expect those who behave similarly to be friends, an incidental memory test was given. Participants were exceptionally likely to falsely remember similarly-behaving partners as friends. Thus, people expect friendship to predict similar behavior and vice versa. These results suggest that knowledge of social networks and others’ behavioral tendencies reciprocally interact to shape social thought and behavior.

Knowledge of someone’s friendships can powerfully impact how one interacts with them. Past research suggests that information about others' real-world social network positions–e.g., how well-connected they are (centrality), 'degrees of separation’ (relative social distance)–is spontaneously encoded when encountering familiar individuals. However, many types of information covary with where someone sits in a social network. For instance, strangers’ face-based trait impressions are associated with their social network centrality, and social distance and centrality are inherently intertwined with familiarity, interpersonal similarity, and memories. To disentangle the encoding of social network position from other social information, participants learned a novel social network in which social network position was decoupled from other factors, then saw each person’s image during functional magnetic resonance imaging scanning. Using representational similarity analysis, we found that social network centrality was robustly encoded in regions associated with visual attention and mentalizing. Thus, even when considering a social network in which one is not included and where centrality was unlinked from perceptual and experience-based features to which it is inextricably tied in naturalistic contexts, the brain encodes information about others’ importance in that network, likely shaping future perceptions of and interactions with those individuals.