Signals of belonging: emergence of signalling norms as facilitators of trust and parochial cooperation.

Mechanisms of social control reinforce norms that appear harmful or wasteful, such as mutilation practises or extensive body tattoos. We suggest such norms arise to serve as signals that distinguish between ingroup 'friends' and outgroup 'foes', facilitating parochial cooperation. Combining insights from research on signalling and parochial cooperation, we incorporate a trust game with signalling in an agent-based model to study the dynamics of signalling norm emergence in groups with conflicting interests. Our results show that costly signalling norms emerge from random acts of signalling in minority groups that benefit most from parochial cooperation. Majority groups are less likely to develop costly signalling norms. Yet, norms that prescribe sending costless group identity signals can easily emerge in groups of all sizes-albeit, at times, at the expense of minority group members. Further, the dynamics of signalling norm emergence differ across signal costs, relative group sizes, and levels of ingroup assortment. Our findings provide theoretical insights into norm evolution in contexts where groups develop identity markers in response to environmental challenges that put their interests at odds with the interests of other groups. Such contexts arise in zones of ethnic conflict or during contestations of existing power relations. This article is part of the theme issue 'Social norm change: drivers and consequences'.

Disease avoidance threatens social cohesion in a large-scale social networking experiment.

People tend to limit social contacts during times of increased health risks, leading to disruption of social networks thus changing the course of epidemics. To what extent, however, do people show such avoidance reactions? To test the predictions and assumptions of an agent-based model on the feedback loop between avoidance behavior, social networks, and disease spread, we conducted a large-scale (2,879 participants) incentivized experiment. The experiment rewards maintaining social relations and structures, and penalizes acquiring infections. We find that disease avoidance dominates networking decisions, despite relatively low penalties for infections; and that participants use more sophisticated strategies than expected (e.g., avoiding susceptible others with infectious neighbors), while they forget to maintain a beneficial network structure. Consequently, we observe low infection numbers, but also deterioration of network positions. These results imply that the focus on a more obvious signal (i.e., infection) may lead to unwanted side effects (i.e., loss of social cohesion).

Social preferences trump emotions in human responses to unfair offers.

People commonly reject unfair offers even if this leaves them worse off. Some explain this as a rational response based on social preferences. Others argue that emotions override self-interest in the determination of rejection behavior. We conducted an experiment in which we measured responders' biophysical reactions (EEG and EMG) to fair and unfair offers. We measured biophysical trait anger using resting-state EEG (frontal alpha-asymmetry), state anger using facial expressions, offer expectancy processing using event-related EEG (medial-frontal negativity; MFN) and self-reported emotions. We systematically varied whether rejections led proposers to lose their share (Ultimatum Game; UG) or not (Impunity Game; IG). Results favor preference-based accounts: Impunity minimizes rejection despite increasing subjectively reported anger. Unfair offers evoke frowning responses, but frowning does not predict rejection. Prosocial responders reject unfair UG offers more often after unmet fairness expectations. These results suggest that responders do not reject unfairness out of anger. Rather, people seem motivated to reject unfair offers when they violate their behavioral code but only when rejection has payoff consequences for the proposer, allowing them to reciprocate and restore equity. Thus, social preferences trump emotions when responding to unfair offers.

The competitive advantage of sanctioning institutions revisited: A multilab replication.

Is peer sanctioning a sustainable solution to the problem of human cooperation? We conducted an exact multilab replication (N = 1,008; 7 labs × 12 groups × 12 participants) of an experiment by Gürerk, Irlenbusch, and Rockenbach published in Science in 2006 (Gürerk Ö, Irlenbusch B, Rockenbach B. The competitive advantage of sanctioning institutions. 2006. Science. 312(5770):108-111). In GIR2006 (N = 84; 1 lab × 7 groups × 12 participants), groups that allowed members to reward cooperators and punish defectors were found to outgrow and outperform groups without a peer-sanctioning institution. We find GIR2006 replicated in accordance with all preregistered replication criteria in five of the seven labs we sampled. There, the majority of participants joined groups with a sanctioning institution, and participants cooperated and profited more on average than in groups without a sanctioning institution. In the two other labs, results were weaker but still favored sanctioning institutions. These findings establish the competitive advantage of sanctioning institutions as a robust phenomenon within the European context.

Improving web-based respondent-driven sampling performance among men who have sex with men in the Netherlands.

Respondent-driven sampling (RDS) uses the social network of participants to sample people of populations that can be challenging to engage. While in this context RDS offers improvements on standard sampling methods, it does not always generate a sufficiently large sample. In this study we aimed to identify preferences of men who have sex with men (MSM) in the Netherlands regarding surveys and recruitment to studies with the subsequent goal of improving the performance of web-based RDS in MSM. A questionnaire about preferences with respect to various aspects of an web-based RDS study was circulated among participants of the Amsterdam Cohort Studies, a study among MSM. The duration of a survey and the type and amount of participation reward were explored. Participants were also asked about their preferences regarding invitation and recruitment methods. We used multi-level and rank-ordered logistic regression to analyze the data and identify the preferences. The majority of the 98 participants were older than 45 years (59.2%), were born in the Netherlands (84.7%), and had a university degree (77.6%). Participants did not have a preference regarding the type of participation reward, but they preferred to spend less time on a survey and to get a higher monetary reward. Sending a personal email was the preferred option to getting invited or inviting someone to a study, while using Facebook messenger was the least preferred option. There are differences between age groups: monetary rewards were less important to older participants (45+) and younger participants (18-34) more often preferred SMS/WhatsApp to recruit others. When designing a web-based RDS study for MSM, it is important to balance the duration of the survey and the monetary reward. If the study takes more of a participants time, it might be beneficial to provide a higher incentive. To optimize expected participation, the recruitment method should be selected based on the targeted population group.

Human cooperation in changing groups in a large-scale public goods game.

How people cooperate to provide public goods is an important scientific question and relates to many societal problems. Previous research studied how people cooperate in stable groups in repeated or one-time-only encounters. However, most real-world public good problems occur in groups with a gradually changing composition due to old members leaving and new members arriving. How group changes are related to cooperation in public good provision is not well understood. To address this issue, we analyze a dataset from an online public goods game comprising approximately 1.5 million contribution decisions made by about 135 thousand players in about 11.3 thousand groups with about 234 thousand changes in group composition. We find that changes in group composition negatively relate to cooperation. Our results suggest that this is related to individuals contributing less in the role of newcomers than in the role of incumbents. During the process of moving from newcomer status to incumbent status, individuals cooperate more and more in line with incumbents.

Health behavior homophily can mitigate the spread of infectious diseases in small-world networks.

Research has repeatedly shown that the spread of infectious diseases is influenced by properties of our social networks. Small-world like structures with densely connected clusters bridged by only a few connections, for example, are not only known to diminish disease spread, but also to increase the chance for a disease to spread to any part of the network. Clusters composed of individuals who show similar reactions to avoid infections (health behavior homophily), however, might change the effect of such clusters on disease spread. To study the combined effect of health behavior homophily and small-world network properties on disease spread, we extend a previously developed ego-centered network formation model and agent-based simulation. Based on more than 80,000 simulated epidemics on generated networks varying in clustering and homophily, as well as diseases varying in severity and infectivity, we predict that the existence of health behavior homophilous clusters reduce the number of infections, lower peak size, and flatten the curve of active cases. That is because agents perceiving higher risks of infections can protect their cluster from infections comparatively quickly by severing only a few bridging ties. A comparison with epidemics in static network structures shows that the incapability to act upon risk perceptions and the low connectivity between clusters in static networks lead to diametrically opposed effects with comparatively large epidemics and prolonged epidemics. These finding suggest that micro-level behavioral adaptation to health risks mitigate macro-level disease spread to an extent that is not captured by static network models of disease spread. Furthermore, this mechanism can be used to design information campaigns targeting proxies for groups with lower risk perception.

Prioritizing high-contact occupations raises effectiveness of vaccination campaigns.

A twenty-year-old idea from network science is that vaccination campaigns would be more effective if high-contact individuals were preferentially targeted. Implementation is impeded by the ethical and practical problem of differentiating vaccine access based on a personal characteristic that is hard-to-measure and private. Here, we propose the use of occupational category as a proxy for connectedness in a contact network. Using survey data on occupation-specific contact frequencies, we calibrate a model of disease propagation in populations undergoing varying vaccination campaigns. We find that vaccination campaigns that prioritize high-contact occupational groups achieve similar infection levels with half the number of vaccines, while also reducing and delaying peaks. The paper thus identifies a concrete, operational strategy for dramatically improving vaccination efficiency in ongoing pandemics.

The effect of competition between health opinions on epidemic dynamics.

Past major epidemic events showed that when an infectious disease is perceived to cause severe health outcomes, individuals modify health behavior affecting epidemic dynamics. To investigate the effect of this feedback relationship on epidemic dynamics, we developed a compartmental model that couples a disease spread framework with competition of two mutually exclusive health opinions (health-positive and health-neutral) associated with different health behaviors. The model is based on the assumption that individuals switch health opinions as a result of exposure to opinions of others through interpersonal communications. To model opinion switch rates, we considered a family of functions and identified the ones that allow health opinions to coexist. Finally, the model includes assortative mixing by opinions. In the disease-free population, either the opinions cannot coexist and one of them is always dominating (mono-opinion equilibrium) or there is at least one stable coexistence of opinions equilibrium. In the latter case, there is multistability between the coexistence equilibrium and the two mono-opinion equilibria. When two opinions coexist, it depends on their distribution whether the infection can invade. If presence of the infection leads to increased switching to a health-positive opinion, the epidemic burden becomes smaller than indicated by the basic reproduction number. Additionally, a feedback between epidemic dynamics and health opinion dynamics may result in (sustained) oscillatory dynamics and a switch to a different stable opinion distribution. Our model captures feedback between spread of awareness through social interactions and infection dynamics and can serve as a basis for more elaborate individual-based models.

A model for the co-evolution of dynamic social networks and infectious disease dynamics.

Recent research shows an increasing interest in the interplay of social networks and infectious diseases. Many studies either neglect explicit changes in health behavior or consider networks to be static, despite empirical evidence that people seek to distance themselves from diseases in social networks. We propose an adaptable steppingstone model that integrates theories of social network formation from sociology, risk perception from health psychology, and infectious diseases from epidemiology. We argue that networking behavior in the context of infectious diseases can be described as a trade-off between the benefits, efforts, and potential harm a connection creates. Agent-based simulations of a specific model case show that: (i) high (perceived) health risks create strong social distancing, thus resulting in low epidemic sizes; (ii) small changes in health behavior can be decisive for whether the outbreak of a disease turns into an epidemic or not; (iii) high benefits for social connections create more ties per agent, providing large numbers of potential transmission routes and opportunities for the disease to travel faster, and (iv) higher costs of maintaining ties with infected others reduce final size of epidemics only when benefits of indirect ties are relatively low. These findings suggest a complex interplay between social network, health behavior, and infectious disease dynamics. Furthermore, they contribute to solving the issue that neglect of explicit health behavior in models of disease spread may create mismatches between observed transmissibility and epidemic sizes of model predictions.

COVID-19 vulnerability and perceived norm violations predict loss of social trust: A pre-post study.

While pandemic containment measures benefit public health, they may jeopardize the social structure of society. We hypothesize that lockdowns and prolonged social distancing measures hinder social support and invite norm violations, eroding social trust. We conducted a pre-registered pre-post study on a representative sample of the Dutch population (n = 2377; participation rate = 88.8%), measuring social trust reported by the same individuals before and after the first wave of the COVID-19 pandemic. Results show that social trust in the Netherlands suddenly dropped from its historically stable level, reaching one of its lowest points on record. The decline was stronger among residents belonging to official high-risk categories, especially if they perceived themselves as likely to become infected. Individuals who more strongly agreed with self-isolation norms or did not perceive a widespread compliance or agreement with such norms also reported a greater loss of trust.

Reputation effects in peer-to-peer online markets: A meta-analysis∗.

Most online market exchanges are governed by reputation systems, which allow traders to comment on one another's behavior and attributes with ratings and text messages. These ratings then constitute sellers' reputations that serve as signals of their trustworthiness and competence. The large body of research investigating the effect of reputation on selling performance has produced mixed results, and there is a lack of consensus on whether the reputation effect exists and what it means. After showing how the reputation effect can be derived from a game-theoretic model, we use meta-analysis to synthesize evidence from 107 studies investigating the reputation effect in peer-to-peer online markets. Our results corroborate the existence of the reputation effect across different operationalizations of seller reputation and selling performance. Our results also show the extent to which the reputation effect varies. We discuss potential explanations for the variation in reputation effects that cannot be attributed to sampling error and thereby point out promising avenues for future research.

Heterogeneous groups cooperate in public good problems despite normative disagreements about individual contribution levels.

Norms can promote human cooperation to provide public goods. Yet, the potential of norms to promote cooperation may be limited to homogeneous groups in which all members benefit equally from the public good. Individual heterogeneity in the benefits of public good provision is commonly conjectured to bring about normative disagreements that harm cooperation. However, the role of these normative disagreements remains unclear because they are rarely directly measured or manipulated. In a laboratory experiment, we first measure participants' views on the appropriate way to contribute to a public good with heterogeneous returns. We then use this information to sort people into groups that either agree or disagree on these views, thereby manipulating group-level disagreement on normative views. Participants subsequently make several incentivized contribution decisions in a public goods game with peer punishment. We find that although there are considerable disagreements about individual contribution levels in heterogeneous groups, these disagreements do not impede cooperation. While cooperation is maintained because low contributors are punished, participants do not use punishment to impose their normative views on others. The contribution levels at which groups cooperate strongly relate to the average normative views of these groups.

Clustering of chronic hepatitis B screening intentions in social networks of Moroccan immigrants in the Netherlands.

BACKGROUND: Early detection, identification, and treatment of chronic hepatitis B through screening is vital for those at increased risk, e.g. born in hepatitis B endemic countries. In the Netherlands, Moroccan immigrants show low participation rates in health-related screening programmes. Since social networks influence health behaviour, we investigated whether similar screening intentions for chronic hepatitis B cluster within social networks of Moroccan immigrants. METHODS: We used respondent-driven sampling (RDS) where each participant ("recruiter") was asked to complete a questionnaire and to recruit three Moroccans ("recruitees") from their social network. Logistic regression analyses were used to analyse whether the recruiters' intention to request a screening test was similar to the intention of their recruitees. RESULTS: We sampled 354 recruiter-recruitee pairs: for 154 pairs both participants had a positive screening intention, for 68 pairs both had a negative screening intention, and the remaining 132 pairs had a discordant intention to request a screening test. A tie between a recruiter and recruitee was associated with having the same screening intention, after correction for sociodemographic variables (OR 1.70 [1.15-2.51]). CONCLUSIONS: The findings of our pilot study show clustering of screening intention among individuals in the same network. This provides opportunities for social network interventions to encourage participation in hepatitis B screening initiatives.

How dominance hierarchies emerge from conflict: A game theoretic model and experimental evidence.

We develop a game theoretic model of conflict and empirically test its predictions to study the emergence of social hierarchies in small groups. Previous research shows uncertainty about actors' ability may lead to more conflict; conflict demonstrates actors' ability and establishes relationships of dominance and submissiveness. Since we assume uncertainty regarding ability to be a crucial cause of conflict, we focus on the effects of different information conditions. We posit that actors know the distribution of abilities in their group and vary whether or not they know (1) their own ability and (2) their interaction partners' interaction histories. Our results from a laboratory experiment closely match qualitative model predictions. Most importantly, conflict produces information about actors' ability, which reduces subsequent conflict. In an exploratory analysis we investigate to what extent gender, social value orientation, risk preferences and a competitive personality account for the quantitative discrepancies between model predictions and subject behavior.

An experimental study of network effects on coordination in asymmetric games.

Network structure has often proven to be important in understanding the decision behavior of individuals or agents in different interdependent situations. Computational studies predict that network structure has a crucial influence on behavior in iterated 2 by 2 asymmetric 'battle of the sexes' games. We test such behavioral predictions in an experiment with 240 human subjects. We found that as expected the less 'random' the network structure, the better the experimental results are predictable by the computational models. In particular, there is an effect of network clustering on the heterogeneity of convergence behavior in the network. We also found that degree centrality and having an even degree are important predictors of the decision behavior of the subjects in the experiment. We thus find empirical validation of predictions made by computational models in a computerized experiment with human subjects.

A stochastic simulation model to study respondent-driven recruitment.

Respondent-driven detection is a chain recruitment method used to sample contact persons of infected persons in order to enhance case finding. It starts with initial individuals, so-called seeds, who are invited for participation. Afterwards, seeds receive a fixed number of coupons to invite individuals with whom they had contact during a specific time period. Recruitees are then asked to do the same, resulting in successive waves of contact persons who are connected in one recruitment tree. However, often the majority of participants fail to invite others, or invitees do not accept an invitation, and recruitment stops after several waves. A mathematical model can help to analyse how various factors influence peer recruitment and to understand under which circumstances sustainable recruitment is possible. We implemented a stochastic simulation model, where parameters were suggested by empirical data from an online survey, to determine the thresholds for obtaining large recruitment trees and the number of waves needed to reach a steady state in the sample composition for individual characteristics. We also examined the relationship between mean and variance of the number of invitations sent out by participants and the probability of obtaining a large recruitment tree. Our main finding is that a situation where participants send out any number of coupons between one and the maximum number is more effective in reaching large recruitment trees, compared to a situation where the majority of participants does not send out any invitations and a smaller group sends out the maximum number of invitations. The presented model is a helpful tool that can assist public health professionals in preparing research and contact tracing using online respondent-driven detection. In particular, it can provide information on the required minimum number of successfully sent invitations to reach large recruitment trees, a certain sample composition or certain number of waves.

Employee cooperative behavior in organizations: a vignette experiment on the relationship between training and helping intentions.

The mutual-investment model predicts a positive relation between investments in training and employees' willingness to behave cooperatively. In this paper, we argue that the extent to which employees increase their cooperative behavior after receiving training depends on the type of training provided, the skillfulness of the employee and the cohesiveness of the team. Focusing on intentions to help coworkers as an indicator for cooperative behavior, we conducted a vignette experiment among 2388 employees working in 127 organizations from four European countries. Multilevel analyses show that training increases employees' intentions to help coworkers. Training promotes helping intentions the most when organizations provide general instead of firm-specific training and when given to employees with limited skills. Whereas employees in cohesive teams indicate higher intentions to help coworkers than employees in non-cohesive teams, training promotes helping intentions equally in both types of teams.

Network effects on coordination in asymmetric games.

Network structure can have an important effect on the behavior of players in an iterated 2 × 2 game. We study the effect of network structure on global and local behavior in asymmetric coordination games using best response dynamics. We find that global behavior is highly dependent on network topology. Random (Erdös-Rényi) networks mostly converge to homogeneous behavior, but the higher the clustering in the network the more heterogeneous the behavior becomes. Behavior within the communities of the network is almost exclusively homogeneous. The findings suggest that clustering of networks facilitates self-organization of uniform behavior within clusters, but heterogeneous behavior between clusters. At the local level we find that some nodes are more important in determining the equilibrium behavior than other nodes. Degree centrality is for most networks the main predictor for the behavior and nodes with an even degree have an advantage over nodes with an uneven degree in dictating the behavior. We conclude that the behavior is difficult to predict for (Erdös-Rényi) networks and that the network imposes the behavior as a function of clustering and degree heterogeneity in other networks.

Consensual punishment does not promote cooperation in the six-person prisoner's dilemma game with noisy public monitoring.

We study the effects of different punishment institutions on cooperation in a six-person prisoner's dilemma game in which actors observe others' cooperation with some noise (i.e. imperfect public monitoring). Previous research has shown that peer punishment can sustain cooperation, if a certain proportion of group members punish defectors at a cost to themselves. However, in the presence of noise, co-operators will sometimes be mistaken for defectors and punished, and defectors will sometimes be mistaken for co-operators and escape punishment. Both types of mistakes are detrimental for cooperation because cooperation is discouraged and defection is encouraged. By means of a laboratory experiment, we study whether this adverse effect of noise can be mitigated by consensual punishment. The more other group members have to agree on punishing a defector, the less likely will a co-operator be punished by mistake. We compare a punishment institution in which each subject decides individually whether to punish another, with institutions in which punishments are only implemented if subjects reach sufficient consensus that a particular group member should be punished. In conditions without noise, we find that cooperation and subjects' payoffs are higher if more consensus is required before a punishment is implemented. In conditions with noise, cooperation is lower if more consensus is required. Moreover, with noise, subjects' payoffs are lower under all punishment institutions than in the control condition without punishment opportunities. Our results narrow down the conditions under which punishment institutions can promote cooperation if such cooperation is noisy.