Sharing the load: Contagion and tolerance of mood in social networks.

The relations between self and others are fluid and constantly changing but exert a profound influence on our identity and emotional experiences. Indeed, human emotions are frequently and intensely social, and the people with whom we interact can alter our momentary mood. But does emotional "contagion" extend over prolonged periods of hours to days, and, if so, how does it propagate through interconnected groups? Answering this question is empirically challenging, because mood similarity in connected individuals can arise through multiple mechanisms (social influence, social selection, and shared external causation), making causal inferences hard to draw. We address this challenge using temporally high-resolution, longitudinal data from 2 independent, bounded social networks during periods of high communal activity and low external contact. Adolescent study participants (N = 79) completed daily mood (n = 4,724) and social interaction (n = 1,775) ratings during residential performance tours of classical music lasting 5 to 7 days. Analyses using statistical network models show that in both networks, adolescent musicians became reciprocally more similar in mood to their interaction partners. The observed contagion effect was greater for negative than for positive mood. That is, although one may catch a friend's bad mood, the friend may feel less negative in the process. These results suggest a mechanism for emotional buffering and the cost of social support. We found no evidence for social selection based on mood. Indeed, participants were remarkably tolerant of their peers' mood fluctuations and showed no evidence of altering their patterns of social interaction accordingly. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Social network-based distancing strategies to flatten the COVID-19 curve in a post-lockdown world.

Social distancing and isolation have been widely introduced to counter the COVID-19 pandemic. Adverse social, psychological and economic consequences of a complete or near-complete lockdown demand the development of more moderate contact-reduction policies. Adopting a social network approach, we evaluate the effectiveness of three distancing strategies designed to keep the curve flat and aid compliance in a post-lockdown world. These are: limiting interaction to a few repeated contacts akin to forming social bubbles; seeking similarity across contacts; and strengthening communities via triadic strategies. We simulate stochastic infection curves incorporating core elements from infection models, ideal-type social network models and statistical relational event models. We demonstrate that a strategic social network-based reduction of contact strongly enhances the effectiveness of social distancing measures while keeping risks lower. We provide scientific evidence for effective social distancing that can be applied in public health messaging and that can mitigate negative consequences of social isolation.

Demographic science aids in understanding the spread and fatality rates of COVID-19.

Governments around the world must rapidly mobilize and make difficult policy decisions to mitigate the coronavirus disease 2019 (COVID-19) pandemic. Because deaths have been concentrated at older ages, we highlight the important role of demography, particularly, how the age structure of a population may help explain differences in fatality rates across countries and how transmission unfolds. We examine the role of age structure in deaths thus far in Italy and South Korea and illustrate how the pandemic could unfold in populations with similar population sizes but different age structures, showing a dramatically higher burden of mortality in countries with older versus younger populations. This powerful interaction of demography and current age-specific mortality for COVID-19 suggests that social distancing and other policies to slow transmission should consider the age composition of local and national contexts as well as intergenerational interactions. We also call for countries to provide case and fatality data disaggregated by age and sex to improve real-time targeted forecasting of hospitalization and critical care needs.

No evidence for kin protection in the expression of sickness behaviors in house mice.

When infected, animals change their behaviors in several ways, including by decreasing their activity, their food and water intake, and their interest in social interactions. These behavioral alterations are collectively called sickness behaviors and, for several decades, the main hypotheses put forward to explain this phenomenon were that engaging in sickness behaviors facilitated the fever response and improved the likelihood of host survival. However, a new hypothesis was recently proposed suggesting that engaging in sickness behaviors may serve to protect kin. We tested this kin protection hypothesis by combining a field and a laboratory experiment in house mice. In both experiments, we induced sickness behaviors by administration of a pro-inflammatory agent. In the field experiment, we then collected genetic data and assessed whether relatedness affected the intensity of sickness behaviors. In the lab experiment, we manipulated relatedness in small social groups and assessed whether having a closely related individual (a sibling) in the group altered social interactions or visits to common resources (such as food and water containers) once immune-challenged. Our results do not support the kinship protection hypothesis and therefore advance our understanding of why such an apparently costly set of behavioral changes would be evolutionarily maintained.

Social interaction and pain: An arctic expedition.

Complex human behaviour can only be understood within its social environment. However, disentangling the causal links between individual outcomes and social network position is empirically challenging. We present a research design in a closed real-world setting with high-resolution temporal data to understand this interplay within a fundamental human experience - physical pain. Study participants completed an isolated 3-week hiking expedition in the Arctic Circle during which they were subject to the same variation in environmental conditions and only interacted amongst themselves. Adolescents provided daily ratings of pain and social interaction partners. Using longitudinal network models, we analyze the interplay between social network position and the experience of pain. Specifically, we test whether experiencing pain is linked to decreasing popularity (increasing isolation), whether adolescents prefer to interact with others experiencing similar pain (homophily), and whether participants are increasingly likely to report similar pain as their interaction partners (contagion). We find that reporting pain is associated with decreasing popularity - interestingly, this effect holds for males only. Further exploratory analyses suggest this is at least partly driven by males withdrawing from contact with females when in pain, enhancing our understanding of pain and masculinity. Contrary to recent experimental and clinical studies, we found no evidence of pain homophily or contagion in the expedition group.

Infection-induced behavioural changes reduce connectivity and the potential for disease spread in wild mice contact networks.

Infection may modify the behaviour of the host and of its conspecifics in a group, potentially altering social connectivity. Because many infectious diseases are transmitted through social contact, social connectivity changes can impact transmission dynamics. Previous approaches to understanding disease transmission dynamics in wild populations were limited in their ability to disentangle different factors that determine the outcome of disease outbreaks. Here we ask how social connectivity is affected by infection and how this relationship impacts disease transmission dynamics. We experimentally manipulated disease status of wild house mice using an immune challenge and monitored social interactions within this free-living population before and after manipulation using automated tracking. The immune-challenged animals showed reduced connectivity to their social groups, which happened as a function of their own behaviour, rather than through conspecific avoidance. We incorporated these disease-induced changes of social connectivity among individuals into models of disease outbreaks over the empirically-derived networks. The models revealed that changes in host behaviour frequently resulted in the disease being contained to very few animals, as opposed to becoming widespread. Our results highlight the importance of considering the role that behavioural alterations during infection can have on social dynamics when evaluating the potential for disease outbreaks.

Relationship Reciprocation Modulates Resource Allocation in Adolescent Social Networks: Developmental Effects.

Adolescence is characterized as a period of social reorientation toward peer relationships, entailing the emergence of sophisticated social abilities. Two studies (Study 1: N = 42, ages 13-17; Study 2: N = 81, ages 13-16) investigated age group differences in the impact of relationship reciprocation within school-based social networks on an experimental measure of cooperation behavior. Results suggest development between mid- and late adolescence in the extent to which reciprocation of social ties predicted resource allocation. With increasing age group, investment decisions increasingly reflected the degree to which peers reciprocated feelings of friendship. This result may reflect social-cognitive development, which could facilitate the ability to navigate an increasingly complex social world in adolescence and promote positive and enduring relationships into adulthood.

Multidimensional Homophily in Friendship Networks.

Homophily - the tendency for individuals to associate with similar others - is one of the most persistent findings in social network analysis. Its importance is established along the lines of a multitude of sociologically relevant dimensions, e.g. sex, ethnicity and social class. Existing research, however, mostly focuses on one dimension at a time. But people are inherently multidimensional, have many attributes and are members of multiple groups. In this article, we explore such multidimensionality further in the context of network dynamics. Are friendship ties increasingly likely to emerge and persist when individuals have an increasing number of attributes in common? We analyze eleven friendship networks of adolescents, draw on stochastic actor-oriented network models and focus on the interaction of established homophily effects. Our results indicate that main effects for homophily on various dimensions are positive. At the same time, the interaction of these homophily effects is negative. There seems to be a diminishing effect for having more than one attribute in common. We conclude that studies of homophily and friendship formation need to address such multidimensionality further.