Triadic influence as a proxy for compatibility in social relationships.

Networks of social interactions are the substrate upon which civilizations are built. Often, we create new bonds with people that we like or feel that our relationships are damaged through the intervention of third parties. Despite their importance and the huge impact that these processes have in our lives, quantitative scientific understanding of them is still in its infancy, mainly due to the difficulty of collecting large datasets of social networks including individual attributes. In this work, we present a thorough study of real social networks of 13 schools, with more than 3,000 students and 60,000 declared positive and negative relationships, including tests for personal traits of all the students. We introduce a metric-the "triadic influence"-that measures the influence of nearest neighbors in the relationships of their contacts. We use neural networks to predict the sign of the relationships in these social networks, extracting the probability that two students are friends or enemies depending on their personal attributes or the triadic influence. We alternatively use a high-dimensional embedding of the network structure to also predict the relationships. Remarkably, using the triadic influence (a simple one-dimensional metric) achieves the best accuracy, and adding the personal traits of the students does not improve the results, suggesting that the triadic influence acts as a proxy for the social compatibility of students. We postulate that the probabilities extracted from the neural networks-functions of the triadic influence and the personalities of the students-control the evolution of real social networks, opening an avenue for the quantitative study of these systems.

Ethnic markers and the emergence of group-specific norms: an experiment.

Visible markers are an important factor in social interactions. Some researchers have argued that one of their roles is to promote cooperation, but models designed to address this issue have yielded contradictory results. Here we present an experimental study of the effect of visible markers on the emergence of social norms where human subjects play a binary coordination game. Our results do not show different, marker-dependent behaviors. Instead, in practically all sessions participants achieved a global equilibrium disregarding the markers. Our findings suggest that simple markers may have a limited role in promoting the emergence of group-dependent social norms and call for further research investigating the role of markers in more sophisticated social settings.

Structural measures of personal networks predict migrants' cultural backgrounds: an explanation from Grid/Group theory.

Culture and social structure are not separated analytical domains but intertwined phenomena observable in personal networks. Drawing on a personal networks dataset of migrants in the United States and Spain, we show that the country of origin, a proxy for diverse languages and cultural institutions, and religion may be predicted by specific combinations of personal network structural measures (closeness, clustering, betweenness, average degree, etc). We obtain similar results applying three different methods (a multinomial logistic regression, a Random Forest algorithm, and an artificial neural network). This finding is explained within the framework of the Grid/Group theory that has long posed the interdependence of social structural and cultural features of human groups.

Ethnic markers and the emergence of group-specific norms.

Observable social traits determine how we interact meaningfully in society even in our globalized world. While a popular hypothesis states that observable traits may help promote cooperation, the alternative explanation that they facilitate coordination has gained ground in recent years. Here we explore this possibility and present a model that investigates the role of ethnic markers in coordination games. In particular, we aim to test the role of reinforcement learning as the microscopic mechanism used by the agents to update their strategies in the game. For a wide range of parameters, we observe the emergence of a collective equilibrium in which markers play an assorting role. However, if individuals are too conformist or too greedy, markers fail to shape social interactions. These results extend and complement previous work focused on agent imitation and show that reinforcement learning is a good candidate to explain many instances where ethnic markers influence coordination.

Competing for congestible goods: experimental evidence on parking choice.

Congestible goods describe situations in which a group of people share or use a public good that becomes congested or overexploited when demand is low. We study experimentally a congestible goods problem of relevance for parking design, namely how people choose between a convenient parking lot with few spots and a less convenient one with unlimited space. We find that the Nash equilibrium predicts reasonably well the competition for the convenient parking when it has few spots, but not when it has more availability. We then show that the Rosenthal equilibrium, a bounded-rational approach, is a better description of the experimental results accounting for the randomness in the decision process. We introduce a dynamical model that shows how Rosenthal equilibria can be approached in a few rounds of the game. Our results give insights on how to deal with parking problems such as the design of parking lots in central locations in cities and open the way to better understand similar congestible goods problems in other contexts.