Personality in the context of social networks

There is great interest in environmental effects on the development and evolution of animal personality traits. An important component of an individual's environment is its social environment. However, few studies look beyond dyadic relationships and try to place the personality of individuals in the context of a social network. Social network analysis provides us with many new metrics to characterize the social fine-structure of populations and, therefore, with an opportunity to gain an understanding of the role that different personalities play in groups, communities and populations regarding information or disease transmission or in terms of cooperation and policing of social conflicts. The network position of an individual is largely a consequence of its interactive strategies. However, the network position can also shape an individual's experiences (especially in the case of juveniles) and therefore can influence the way in which it interacts with others in future. Finally, over evolutionary time, the social fine-structure of animal populations (as quantified by social network analysis) can have important consequences for the evolution of personalities-an approach that goes beyond the conventional game-theoretic analyses that assumed random mixing of individuals in populations.     

Trust transitivity in social networks

Non-centralized recommendation-based decision making is a central feature of several social and technological processes, such as market dynamics, peer-to-peer file-sharing and the web of trust of digital certification. We investigate the properties of trust propagation on networks, based on a simple metric of trust transitivity. We investigate analytically the percolation properties of trust transitivity in random networks with arbitrary in/out-degree distributions, and compare with numerical realizations. We find that the existence of a non-zero fraction of absolute trust (i.e. entirely confident trust) is a requirement for the viability of global trust propagation in large systems: The average pair-wise trust is marked by a discontinuous transition at a specific fraction of absolute trust, below which it vanishes. Furthermore, we perform an extensive analysis of the Pretty Good Privacy (PGP) web of trust, in view of the concepts introduced. We compare different scenarios of trust distribution: community- and authority-centered. We find that these scenarios lead to sharply different patterns of trust propagation, due to the segregation of authority hubs and densely-connected communities. While the authority-centered scenario is more efficient, and leads to higher average trust values, it favours weakly-connected "fringe" nodes, which are directly trusted by authorities. The community-centered scheme, on the other hand, favours nodes with intermediate in/out-degrees, in detriment of the authorities and its "fringe" peers.     

Detecting social transmission in networks

In recent years researchers have drawn attention to a need for new methods with which to identify the spread of behavioural innovations through social transmission in animal populations. Network-based analyses seek to recognise diffusions mediated by social learning by detecting a correspondence between patterns of association and the flow of information through groups. Here we introduce a new order of acquisition diffusion analysis (OADA) and develop established time of acquisition diffusion analysis (TADA) methods further. Through simulation we compare the merits of these and other approaches, demonstrating that OADA and TADA have greater power and lower Type I error rates than available alternatives, and specifying when each approach should be deployed. We illustrate the new methods by applying them to reanalyse an established dataset corresponding to the diffusion of foraging innovations in starlings, where OADA and TADA detect social transmission that hitherto had been missed. The methods are potentially widely applicable by researchers wishing to detect social learning in natural and captive populations of animals, and to facilitate this we provide code to implement OADA and TADA in the statistical package R.     

Institutions,information exchange,and migrant social networks in Rome

While a considerable body of work examines immigrant networks, inadequate attention has been devoted to understanding how networks regulate the relationship between immigrants and host institutions. A rich immigrant process may reinforce current power structures by providing a convenient buffer between the elite and challengers. Conversely, immigration may challenge the status quo. I employ social network analysis to examine three understudied immigrant groups in Rome, Bangladeshis, Filipinos, and Peruvians. I find that they have developed systems of problem-solving and sense-making that often interrupt their interactions with host institutions. The state tolerates this because it situates immigrants’ concerns outside its sphere of responsibility.     

Hypothesis testing in animal social networks

Behavioural ecologists are increasingly using social network analysis to describe the social organisation of animal populations and to test hypotheses. However, the statistical analysis of network data presents a number of challenges. In particular the non-independent nature of the data violates the assumptions of many common statistical approaches. In our opinion there is currently confusion and uncertainty amongst behavioural ecologists concerning the potential pitfalls when hypotheses testing using social network data. Here we review what we consider to be key considerations associated with the analysis of animal social networks and provide a practical guide to the use of null models based on randomisation to control for structure and non-independence in the data.     

Information processing in social insect networks

Investigating local-scale interactions within a network makes it possible to test hypotheses about the mechanisms of global network connectivity and to ask whether there are general rules underlying network function across systems. Here we use motif analysis to determine whether the interactions within social insect colonies resemble the patterns exhibited by other animal associations or if they exhibit characteristics of biological regulatory systems. Colonies exhibit a predominance of feed-forward interaction motifs, in contrast to the densely interconnected clique patterns that characterize human interaction and animal social networks. The regulatory motif signature supports the hypothesis that social insect colonies are shaped by selection for network patterns that integrate colony functionality at the group rather than individual level, and demonstrates the utility of this approach for analysis of selection effects on complex systems across biological levels of organization.     

Threshold learning dynamics in social networks

Social learning is defined as the ability of a population to aggregate information, a process which must crucially depend on the mechanisms of social interaction. Consumers choosing which product to buy, or voters deciding which option to take with respect to an important issue, typically confront external signals to the information gathered from their contacts. Economic models typically predict that correct social learning occurs in large populations unless some individuals display unbounded influence. We challenge this conclusion by showing that an intuitive threshold process of individual adjustment does not always lead to such social learning. We find, specifically, that three generic regimes exist separated by sharp discontinuous transitions. And only in one of them, where the threshold is within a suitable intermediate range, the population learns the correct information. In the other two, where the threshold is either too high or too low, the system either freezes or enters into persistent flux, respectively. These regimes are generally observed in different social networks (both complex or regular), but limited interaction is found to promote correct learning by enlarging the parameter region where it occurs.     

Effects of deception in social networks

Honesty plays a crucial role in any situation where organisms exchange information or resources. Dishonesty can thus be expected to have damaging effects on social coherence if agents cannot trust the information or goods they receive. However, a distinction is often drawn between prosocial lies (‘white’ lies) and antisocial lying (i.e. deception for personal gain), with the former being considered much less destructive than the latter. We use an agent-based model to show that antisocial lying causes social networks to become increasingly fragmented. Antisocial dishonesty thus places strong constraints on the size and cohesion of social communities, providing a major hurdle that organisms have to overcome (e.g. by evolving counter-deception strategies) in order to evolve large, socially cohesive communities. In contrast, white lies can prove to be beneficial in smoothing the flow of interactions and facilitating a larger, more integrated network. Our results demonstrate that these group-level effects can arise as emergent properties of interactions at the dyadic level. The balance between prosocial and antisocial lies may set constraints on the structure of social networks, and hence the shape of society as a whole.     

Entropy of dynamical social networks

Human dynamical social networks encode information and are highly adaptive. To characterize the information encoded in the fast dynamics of social interactions, here we introduce the entropy of dynamical social networks. By analysing a large dataset of phone-call interactions we show evidence that the dynamical social network has an entropy that depends on the time of the day in a typical week-day. Moreover we show evidence for adaptability of human social behavior showing data on duration of phone-call interactions that significantly deviates from the statistics of duration of face-to-face interactions. This adaptability of behavior corresponds to a different information content of the dynamics of social human interactions. We quantify this information by the use of the entropy of dynamical networks on realistic models of social interactions.     

Assortative interactions and social networks in fish

The mechanisms underpinning the structure of social networks in multiple fish populations were investigated. To our knowledge this is the first study to provide replication of social networks and therefore probably the first that allows general conclusions to be drawn. The social networks were all found to have a non-random structure and exhibited social cliquishness. A number of factors were observed to contribute to this structuring. Firstly, social network structure was influenced by body length and shoaling tendency, with individuals interacting more frequently with conspecifics of similar body length and shoaling tendency. Secondly, individuals with many social contacts were found to interact with each other more often than with other conspecifics, a phenomenon known as a positive degree correlation. Finally, repeated interactions between pairs of individuals occurred within the networks more often than expected by random interactions. The observed network structures will have ecological and evolutionary implications. For example, the occurrence of positive degree correlations suggests the possibility that pathogens and information (that are socially transmitted) could spread very fast within the populations. Furthermore, the occurrence of repeated interactions between pairs of individuals fulfils an important pre-requisite for the evolution of reciprocal altruism.     

Men's social networks and contraception in Ghana

In this paper, longitudinal data from northern Ghana is used to assess the effects of encouragement to use family planning that men receive from their personal network partners on the adoption of modern contraception by their wives. The study tests a conceptual model that, in addition to the effect of men's network encouragement, incorporates the effect of encouragement to use family planning that women receive from their respective network partners and the effect of spousal communication on reproductive matters and approval of family planning. Results show that encouragement received by men from their social networks significantly increases the likelihood of subsequent contraceptive use by their wives but this effect operates primarily by galvanizing spousal communication on reproductive matters. The effect of encouragement received by women from their respective network partners is largely independent from the effect of male network encouragement but it influences contraceptive adoption both directly and through spousal communication.     

The building-up of social relationships: behavioural types, social networks and cooperative breeding in a cichlid

Consistent individual differences in behavioural types may not only cause variation in life-history decisions, but may also affect the choice of social partners and sociality in general. Here, we tested whether and how behavioural type influences the establishment of social ties using the cooperatively breeding cichlid, Neolamprologus pulcher. In a habitat saturation experiment with individuals pre-tested for behavioural type, we first analysed whether behavioural type affected the likelihood of settlement (i.e. social status), group sizes, and the types of dominant and subordinate individuals accepted as group members. Corrected for effects of body size and sex, the behavioural type did not affect settlement. However, bold dominant males only accepted smaller females, and grouped with bold subordinates, while shy dominant males accepted larger females than themselves, and grouped with shy subordinates. Second, we analysed the relationships between behavioural type and the aggressiveness or affiliation social network. Behavioural type significantly affected the number and quality of connections within the two networks. We show that behavioural types affect group composition, social networks and status achieved, in interaction with body size. Thus, the interactions within groups may depend not only on age, size and sex, but also on the behavioural type of the individuals involved.     

Social networks and the development of social skills in cowbirds

The complex interrelationships among individuals within social environments can exert selection pressures on social skills: those behaviours and cognitive processes that allow animals to manipulate and out-reproduce others. Social complexity can also have a developmental effect on social skills by providing individuals with opportunities to hone their skills by dealing with the challenges posed in within-group interactions. We examined how social skills develop in captive, adult male brown-headed cowbirds (Molothrus ater) that were exposed to differing levels of 'social complexity' across a 2-year experiment. After each year, subjects housed in groups with dynamic social structure (where many individuals entered and exited the groups during the year) outcompeted birds who had been housed in static groups. Exposure to dynamic structure subsequently led to substantial changes to the social networks of the home conditions during the breeding season. Static groups were characterized by a predictable relationship between singing and reproductive success that was stable across years. In dynamic conditions, however, males showed significant variability in their dominance status, their courting and even in their mating success. Reproductive success of males varied dramatically across years and was responsive to social learning in adulthood, and socially dynamic environments 'trained' individuals to be better competitors, even at an age when the development of many traits important for breeding (like song quality) had ended.     

Spreading of healthy mood in adolescent social networks

Depression is a major public health concern worldwide. There is evidence that social support and befriending influence mental health, and an improved understanding of the social processes that drive depression has the potential to bring significant public health benefits. We investigate transmission of mood on a social network of adolescents, allowing flexibility in our model by making no prior assumption as to whether it is low mood or healthy mood that spreads. Here, we show that while depression does not spread, healthy mood among friends is associated with significantly reduced risk of developing and increased chance of recovering from depression. We found that this spreading of healthy mood can be captured using a non-linear complex contagion model. Having sufficient friends with healthy mood can halve the probability of developing, or double the probability of recovering from, depression over a 6–12-month period on an adolescent social network. Our results suggest that promotion of friendship between adolescents can reduce both incidence and prevalence of depression.     

Encrypted humor and social networks in rural Brazil

The encryption theory of humor (Flamson & Barrett, 2008) proposes that one of the means by which people develop their social networks is assortment with the most compatible peers by signaling similarity in locally variable personal features through humor. Here we present experimental and observational evidence obtained on a collective farm in rural Brazil, where participants were presented with high- and low-encryption versions of jokes after assessing their prior knowledge, and completed a photo-sorting task to determine the structure of their social networks. These results, replicating previous findings using online surveys, demonstrated a significant effect of prior knowledge and some of the predicted interactions between prior knowledge and encryption level, as well as a small but significant effect of social closeness on similarity in joke ratings. Taken together, these findings support the hypotheses that (a) the cognitive processing of humor relies on an encryption–decryption process, (b) similarity in humor preferences reflects similarities in those cognitive processes and (c) that similarity plays a role in real-world social assortment.     

From local to global dilemmas in social networks

Social networks affect in such a fundamental way the dynamics of the population they support that the global, population-wide behavior that one observes often bears no relation to the individual processes it stems from. Up to now, linking the global networked dynamics to such individual mechanisms has remained elusive. Here we study the evolution of cooperation in networked populations and let individuals interact via a 2-person Prisoner's Dilemma--a characteristic defection dominant social dilemma of cooperation. We show how homogeneous networks transform a Prisoner's Dilemma into a population-wide evolutionary dynamics that promotes the coexistence between cooperators and defectors, while heterogeneous networks promote their coordination. To this end, we define a dynamic variable that allows us to track the self-organization of cooperators when co-evolving with defectors in networked populations. Using the same variable, we show how the global dynamics--and effective dilemma--co-evolves with the motifs of cooperators in the population, the overall emergence of cooperation depending sensitively on this co-evolution.