Social network architecture and the maintenance of deleterious cultural traits.

How have changes in communications technology affected the way that misinformation spreads through a population and persists? To what extent do differences in the architecture of social networks affect the spread of misinformation, relative to the rates and rules by which individuals transmit or eliminate different pieces of information (cultural traits)? Here, we use analytical models and individual-based simulations to study how a 'cultural load' of misinformation can be maintained in a population under a balance between social transmission and selective elimination of cultural traits with low intrinsic value. While considerable research has explored how network architecture affects percolation processes, we find that the relative rates at which individuals transmit or eliminate traits can have much more profound impacts on the cultural load than differences in network architecture. In particular, the cultural load is insensitive to correlations between an individual's network degree and rate of elimination when these quantities vary among individuals. Taken together, these results suggest that changes in communications technology may have influenced cultural evolution more strongly through changes in the amount of information flow, rather than the details of who is connected to whom.

Information sharing and social network dynamics : a coevolutionary approach

The capacity to interact socially and share information underlies the success of many animal species, humans included. Researchers of many fields have emphasized the evo¬lutionary significance of how patterns of connections between individuals, or the social networks, and learning abilities affect the information obtained by animal societies. To date, studies have focused on the dynamics either of social networks, or of the spread of information. The present work aims to study them together. We make use of mathematical and computational models to study the dynamics of networks, where social learning and information sharing affect the structure of the population the individuals belong to. The number and strength of the relationships between individuals, in turn, impact the accessibility and the diffusion of the shared information. Moreover, we inves¬tigate how different strategies in the evaluation and choice of interacting partners impact the processes of knowledge acquisition and social structure rearrangement. First, we look at how different evaluations of social interactions affect the availability of the information and the network topology. We compare a first case, where individuals evaluate social exchanges by the amount of information that can be shared by the partner, with a second case, where they evaluate interactions by considering their partners' social status. We show that, even if both strategies take into account the knowledge endowments of the partners, they have very different effects on the system. In particular, we find that the first case generally enables individuals to accumulate higher amounts of information, thanks to the more efficient patterns of social connections they are able to build. Then, we study the effects that homophily, or the tendency to interact with similar partners, has on knowledge accumulation and social structure. We compare the case where individuals who know the same information are more likely to learn socially from each other, to the opposite case, where individuals who know different information are instead more likely to learn socially from each other. We find that it is not trivial to claim which strategy is better than the other. Depending on the possibility of forgetting information, the way new social partners can be chosen, and the population size, we delineate the conditions for which each strategy allows accumulating more information, or in a faster way For these conditions, we also discuss the topological characteristics of the resulting social structure, relating them to the information dynamics outcome. In conclusion, this work paves the road for modeling the joint dynamics of the spread of information among individuals and their social interactions. It also provides a formal framework to study jointly the effects of different strategies in the choice of partners on social structure, and how they favor the accumulation of knowledge in the population. - La capacité d'interagir socialement et de partager des informations est à la base de la réussite de nombreuses espèces animales, y compris les humains. Les chercheurs de nombreux domaines ont souligné l'importance évolutive de la façon dont les modes de connexions entre individus, ou réseaux sociaux et les capacités d'apprentissage affectent les informations obtenues par les sociétés animales. À ce jour, les études se sont concentrées sur la dynamique soit des réseaux sociaux, soit de la diffusion de l'information. Le présent travail a pour but de les étudier ensemble. Nous utilisons des modèles mathématiques et informatiques pour étudier la dynamique des réseaux, où l'apprentissage social et le partage d'information affectent la structure de la population à laquelle les individus appartiennent. Le nombre et la solidité des relations entre les individus ont à leurs tours un impact sur l'accessibilité et la diffusion de l'informa¬tion partagée. Par ailleurs, nous étudions comment les différentes stratégies d'évaluation et de choix des partenaires d'interaction ont une incidence sur les processus d'acquisition des connaissances ainsi que le réarrangement de la structure sociale. Tout d'abord, nous examinons comment des évaluations différentes des interactions sociales influent sur la disponibilité de l'information ainsi que sur la topologie du réseau. Nous comparons un premier cas, où les individus évaluent les échanges sociaux par la quantité d'information qui peut être partagée par le partenaire, avec un second cas, où ils évaluent les interactions en tenant compte du statut social de leurs partenaires. Nous montrons que, même si les deux stratégies prennent en compte le montant de connaissances des partenaires, elles ont des effets très différents sur le système. En particulier, nous constatons que le premier cas permet généralement aux individus d'accumuler de plus grandes quantités d'information, grâce à des modèles de connexions sociales plus efficaces qu'ils sont capables de construire. Ensuite, nous étudions les effets que l'homophilie, ou la tendance à interagir avec des partenaires similaires, a sur l'accumulation des connaissances et la structure sociale. Nous comparons le cas où des personnes qui connaissent les mêmes informations sont plus sus¬ceptibles d'apprendre socialement l'une de l'autre, au cas où les individus qui connaissent des informations différentes sont au contraire plus susceptibles d'apprendre socialement l'un de l'autre. Nous constatons qu'il n'est pas trivial de déterminer quelle stratégie est meilleure que l'autre. En fonction de la possibilité d'oublier l'information, la façon dont les nouveaux partenaires sociaux peuvent être choisis, et la taille de la population, nous déterminons les conditions pour lesquelles chaque stratégie permet d'accumuler plus d'in¬formations, ou d'une manière plus rapide. Pour ces conditions, nous discutons également les caractéristiques topologiques de la structure sociale qui en résulte, les reliant au résultat de la dynamique de l'information. En conclusion, ce travail ouvre la route pour la modélisation de la dynamique conjointe de la diffusion de l'information entre les individus et leurs interactions sociales. Il fournit également un cadre formel pour étudier conjointement les effets de différentes stratégies de choix des partenaires sur la structure sociale et comment elles favorisent l'accumulation de connaissances dans la population.

A Social Network Analysis of Twitter: Mapping the Digital Humanities Community

Defining digital humanities might be an endless debate if we stick to the discussion about the boundaries of this concept as an academic "discipline". In an attempt to concretely identify this field and its actors, this paper shows that it is possible to analyse them through Twitter, a social media widely used by this "community of practice". Based on a network analysis of 2,500 users identified as members of this movement, the visualisation of the "who's following who?" graph allows us to highlight the structure of the network's relationships, and identify users whose position is particular. Specifically, we show that linguistic groups are key factors to explain clustering within a network whose characteristics look similar to a small world.

How central and connected am I in my family? Bridging and bonding social capital in family configurations of young adults with psychiatric disorders

AIMS: This article explores the structures of relational resources that individuals with psychiatric disorders get from their family configurations using the concept of social capital. METHODS: The research is based on a sample of 54 individuals with psychiatric disorders and behavioural problems, and a comparison sample of 54 individuals without a clinical record matched to the clinical respondents for age and sex. Standard measures of social capital from social network methods are applied on family configurations of individuals from both samples. Differences are tested by variance analysis. RESULTS: Structures of family resources available to individuals with psychiatric disorders are distinct. Individuals with psychiatric disorders perceive themselves as less central in their family configurations and less connected to their family members. Their significant family members are perceived as less connected with each other. As a whole, their family configurations are smaller and do not include spouses or partners. Therefore bridging and bonding social capitals are not readily available for them. CONCLUSION: As family configurations of individuals with psychiatric disorders provide fewer relational resources than other families, they are not able to deal with social integration of individuals with psychiatric disorders on their own.

Social Interaction Effects on Fertility: Intentions and Behaviors

The existing literature shows that social interactions in individuals' networks affect their reproductive attitudes and behaviors through three mechanisms: social influence, social learning, and social support. In this paper, we discuss to what extent the Theory of Planned Behavior (TPB), an individual based theorization of intentions and behavior used to model fertility, takes these social mechanisms into account. We argue that the TPB already integrates social influence and that it could easily accommodate the two other social network mechanisms. By doing so, the theory would be enriched in two respects. First, it will explain more completely how macro level changes eventually ends in micro level changes in behavioral intentions. Indeed, mechanisms of social influence may explain why changes in representations of parenthood and ideal family size can be slower than changes in socio-economic conditions and institutions. Social learning mechanisms should also be considered, since they are crucial to distinguish who adopts new behavioral beliefs and practices, when change at the macro level finally sinks in. Secondly, relationships are a capital of services that can complement institutional offering (informal child care) as well as a capital of knowledge which help individuals navigate in a complex institutional reality, providing a crucial element to explain heterogeneity in the successful realization of fertility intentions across individuals. We develop specific hypotheses concerning the effect of social interactions on fertility intentions and their realization to conclude with a critical review of the existing surveys suitable to test them and their limits.

Développement des compétences et des cerlces sociaux à l'adolescence : conséquances des interactions médiatisées par ordinateur

Ce travail porte sur le développement des compétences sociales et des cercles sociaux à l'adolescence. Il s'intéresse plus particulièrement à l'effet au cours du temps que peuvent avoir les nouveaux moyens de communication électronique (MCE) sur ces deux aspects de la socialisation. Trois parties principales se dégagent de ce travail. La première partie présente le développement d'un outil multidimensionnel destiné à l'évaluation des compétences sociales et permettant de les distinguer en fonction du contexte d'interaction (online vs. offline). La seconde partie porte sur la comparaison des compétences sociales et de la taille du cercle social de 329 adolescents de 7e et de 8e année primaire, en fonction de leur utilisation, ou non, des MCE. Elle met en évidence que ces deux aspects diffèrent de manière statistiquement significative entre les deux groupes, en faveur des utilisateurs de MCE. La troisième partie se centre sur l'utilisation de différents MCE et sur les effets différentiels qu'ils peuvent avoir au cours du temps sur ces deux aspects de la socialisation. Les analyses des données longitudinales mettent en évidence que l'utilisation de sites de réseaux sociaux (SRS) est particulièrement susceptible d'améliorer les compétences sociales et d'augmenter la taille du cercle social. Un modèle dans lequel les compétences sociales jouent un rôle de médiateur entre l'utilisation de SRS et la taille du cercle social est finalement postulé. - This work's topic concerns the development of social skills and social network size during adolescence. It examines more particularly the effects that new online communication media (OCM) may have on these two aspects of adolescent socialization. It is subdivided in three distinct parts. The first part presents the development of a multidimensional tool designed to assess social skills in two different contexts of interaction (online vs. offline). The second part compares the social skills and social network size of 329 adolescents depending on their use, or not, of OCM. It highlights significant differences on these two aspects between users and non-users, in favor of OCM users. The third part focuses on the differential effects that six OCM may have over time on these two aspects of socialization. Longitudinal data analyses highlight that the use of social network sites (SNS) is particularly likely to improve social skills and to increase social network size. A model in which social skills mediate the relationship between SNS use and social network size is finally postulated.

Firm's network capability and innovation performance: evidences from China hi-tech industry

ABSTRACT : A firm's competitive advantage can arise from internal resources as well as from an interfirm network. -This dissertation investigates the competitive advantage of a firm involved in an innovation network by integrating strategic management theory and social network theory. It develops theory and provides empirical evidence that illustrates how a networked firm enables the network value and appropriates this value in an optimal way according to its strategic purpose. The four inter-related essays in this dissertation provide a framework that sheds light on the extraction of value from an innovation network by managing and designing the network in a proactive manner. The first essay reviews research in social network theory and knowledge transfer management, and identifies the crucial factors of innovation network configuration for a firm's learning performance or innovation output. The findings suggest that network structure, network relationship, and network position all impact on a firm's performance. Although the previous literature indicates that there are disagreements about the impact of dense or spare structure, as well as strong or weak ties, case evidence from Chinese software companies reveals that dense and strong connections with partners are positively associated with firms' performance. The second essay is a theoretical essay that illustrates the limitations of social network theory for explaining the source of network value and offers a new theoretical model that applies resource-based view to network environments. It suggests that network configurations, such as network structure, network relationship and network position, can be considered important network resources. In addition, this essay introduces the concept of network capability, and suggests that four types of network capabilities play an important role in unlocking the potential value of network resources and determining the distribution of network rents between partners. This essay also highlights the contingent effects of network capability on a firm's innovation output, and explains how the different impacts of network capability depend on a firm's strategic choices. This new theoretical model has been pre-tested with a case study of China software industry, which enhances the internal validity of this theory. The third essay addresses the questions of what impact network capability has on firm innovation performance and what are the antecedent factors of network capability. This essay employs a structural equation modelling methodology that uses a sample of 211 Chinese Hi-tech firms. It develops a measurement of network capability and reveals that networked firms deal with cooperation between, and coordination with partners on different levels according to their levels of network capability. The empirical results also suggests that IT maturity, the openness of culture, management system involved, and experience with network activities are antecedents of network capabilities. Furthermore, the two-group analysis of the role of international partner(s) shows that when there is a culture and norm gap between foreign partners, a firm must mobilize more resources and effort to improve its performance with respect to its innovation network. The fourth essay addresses the way in which network capabilities influence firm innovation performance. By using hierarchical multiple regression with data from Chinese Hi-tech firms, the findings suggest that there is a significant partial mediating effect of knowledge transfer on the relationships between network capabilities and innovation performance. The findings also reveal that the impacts of network capabilities divert with the environment and strategic decision the firm has made: exploration or exploitation. Network constructing capability provides a greater positive impact on and yields more contributions to innovation performance than does network operating capability in an exploration network. Network operating capability is more important than network constructing capability for innovative firms in an exploitation network. Therefore, these findings highlight that the firm can shape the innovation network proactively for better benefits, but when it does so, it should adjust its focus and change its efforts in accordance with its innovation purposes or strategic orientation.

What keeps female problematic internet users busy online?

While problematic Internet use is recognized to be predominant among male adolescents, a female trend is gradually becoming apparent. Our study aimed at investigating the characteristics of female Internet users and distinguishing between the online activities of problematic and regular Internet users' on school days. Data were retrieved from a cross-sectional survey of a representative sample of 3067 8th graders in the canton of Vaud, Switzerland, that completed an online questionnaire in 2012. Only females were included. Based on the Internet addiction test, the sample was divided into regular (RUs) (IAT < 50, n = 1339) and problematic users (PIUs) (IAT ≥ 50, n = 201). Groups were compared regarding sociodemographic variables, online activities, devices used to access the Internet, substance use, and physical activity. Significant variables were included in a backward logistic regression. At the multivariate level, PIUs were more prone to spend time online for leisure activities (odds ratio [OR] 2.38) and to access the Internet through a smartphone (OR 1.79) or tablet (OR 1.84). PIUs were less likely to be physically active (OR 0.86) and more likely to present poor emotional well-being (OR 2.67) and to smoke (OR 1.88). CONCLUSION: A sizeable percentage of female adolescents are problematic Internet users. When performing a comprehensive biopsychosocial assessment, teenagers owning numerous devices to access the Internet, presenting other health-compromising behaviors or poor emotional well-being should be specifically targeted. WHAT IS KNOWN: ? Problematic Internet use has been found to be predominant among males. ? Specific online activities have been identified as being addictive for young men and women differently. ? Problematic Internet use is known to impact in several ways the general health and daily functioning of teenagers. What is New: ? A sizeable percentage of female adolescents are problematic Internet users. ? Tobacco use, poor well-being, as well as compact devices to access the Internet are positively related to problematic Internet use. ? In addition to their special interest in online social and communicational activities, female problematic Internet users also reported more online gambling.

L'apport de la trace matérielle dans l'enquête criminelle: évaluation de la contribution des liens chimiques issus du profilage de produits stupéfiants par l'analyse des réseaux sociaux

La trace matérielle dispose d'un potentiel incomparable pour mettre en relation des indices et occupe souvent une place centrale lors du procès pénal (Ribaux et Margot, 2008). Au delà de son rôle élémentaire en tant qu'élément de preuve, la trace matérielle véhicule de nombreuses autres informations encore trop peu exploitées en matière d'investigation ou pour servir de base au renseignement criminel. C'est particulièrement le cas des liens chimiques découverts grâce au profilage physico-chimique de produits stupéfiants saisis par les autorités. Le but de ce travail est d'estimer l'apport de ces liens chimiques à la perception de la structure des réseaux criminels. Pour ce faire, nous nous appuyons sur des modèles d'analyse des réseaux sociaux (SNA, Social Network Analysis). Ces modèles sont toujours plus utilisés pour traiter des affaires qui relèvent de la criminalité organisée, notamment pour comprendre la structure et la dynamique de ces réseaux d'acteurs. L'analyse des réseaux sociaux (SNA) procède par le calcul de différents indicateurs pour mettre en évidence des éléments pertinents de leur structure et leurs acteurs clés. Par exemple, l'identification des vulnérabilités de l'organisation et des mécanismes mis en place par les acteurs pourra orienter les actions policières. Cette recherche se base sur une enquête concernant un réseau international de trafic de produits stupéfiants. En plus des autres informations d'enquête traditionnellement disponibles, des liens chimiques ont été mis en évidence par le profilage de l'héroïne saisie à différents endroits et périodes, puis utilisés par les enquêteurs. Cette recherche consiste à utiliser les indicateurs SNA pour évaluer l'influence de ces liens chimiques sur la structure de ce réseau construit à partir des autres indices. Les premiers résultats montrent que les liens chimiques sont cohérents avec les autres types de relations, et qu'ils tendent, à eux seuls, à mettre en évidence les positions centrales de certains acteurs clés. De plus, l'intégration de ces liens renforce les centralités de certains acteurs et permet ainsi de les considérer de manière plus centrale qu'ils ne l'étaient auparavant. Enfin, ces premiers résultats laissent entrevoir des perspectives intéressantes notamment au travers de la pondération de ces relations afin d'évaluer de manière plus globale l'apport du potentiel informatif de ce type de renseignement.

Having Your Cake and Eating It, Too: Can Regulatory Agencies Be Both Independent and Accountable?

Independent regulatory agencies (IRAs) were created in various sectors and on different governmental levels to implement liberalization policies. This paper investigates the link between IRAs' independence, which is said to promote regulatory credibility and the use of technical expertise, and their accountability, which is related to the need for controlling and legitimizing independent regulators. The literature on the regulatory state anticipates a positive relation between the independence and accountability of IRAs, but systematic empirical evidence is still lacking. To tackle this question, this paper measures and compares the independence and the accountability of IRAs in three differentially liberalized sectors in Switzerland (telecommunications, electricity and railways). With the application of Social Network Analysis, this piece of research shows that IRAs can be de facto independent and accountable at the same time, but the two features do not necessarily co-evolve in the same direction.

From Support to Control : A Configurational Perspective on Conjugal Quality

The topic of conjugal quality provides an empirical illustration of the relevance of the configurational perspective on families. Based on a longitudinal sample of 1,534 couples living in Switzerland drawn from the study "Social Stratification, Cohesion and Conflict in Contemporary Families", we show that various types of interdependencies with relatives and friends promote distinct conflict management strategies for couples as well as unequal levels of conjugal quality. We find that configurations characterized by supportive and non-interfering relationships with relatives and friends for both partners are associated with higher conjugal quality, while configurations characterized by interference are associated with lower conjugal quality.

Kinship in entrepreneur networks: Performance effects of resource assembly in Africa

We examine the relationship between structural social capital, resource assembly, and firm performance of entrepreneurs in Africa. We posit that social capital primarily composed of kinship or family ties helps the entrepreneur to raise resources, but it does so at a cost. Using data drawn from small firms in Kampala, Uganda, we explore how shared identity among the entrepreneur's social network moderates this relationship. A large network contributed a higher quantity of resources raised, but at a higher cost when shared identity was high. We discuss the implications of these findings for the role of family ties and social capital in resource assembly, with an emphasis on developing economies.

Character Networks and Centrality

A character network represents relations between characters from a text; the relations are based on text proximity, shared scenes/events, quoted speech, etc. Our project sketches a theoretical framework for character network analysis, bringing together narratology, both close and distant reading approaches, and social network analysis. It is in line with recent attempts to automatise the extraction of literary social networks (Elson, 2012; Sack, 2013) and other studies stressing the importance of character- systems (Woloch, 2003; Moretti, 2011). The method we use to build the network is direct and simple. First, we extract co-occurrences from a book index, without the need for text analysis. We then describe the narrative roles of the characters, which we deduce from their respective positions in the network, i.e. the discourse. As a case study, we use the autobiographical novel Les Confessions by Jean-Jacques Rousseau. We start by identifying co-occurrences of characters in the book index of our edition (Slatkine, 2012). Subsequently, we compute four types of centrality: degree, closeness, betweenness, eigenvector. We then use these measures to propose a typology of narrative roles for the characters. We show that the two parts of Les Confessions, written years apart, are structured around mirroring central figures that bear similar centrality scores. The first part revolves around the mentor of Rousseau; a figure of openness. The second part centres on a group of schemers, depicting a period of deep paranoia. We also highlight characters with intermediary roles: they provide narrative links between the societies in the life of the author. The method we detail in this complete case study of character network analysis can be applied to any work documented by an index. Un réseau de personnages modélise les relations entre les personnages d'un récit : les relations sont basées sur une forme de proximité dans le texte, l'apparition commune dans des événements, des citations dans des dialogues, etc. Notre travail propose un cadre théorique pour l'analyse des réseaux de personnages, rassemblant narratologie, close et distant reading, et analyse des réseaux sociaux. Ce travail prolonge les tentatives récentes d'automatisation de l'extraction de réseaux sociaux tirés de la littérature (Elson, 2012; Sack, 2013), ainsi que les études portant sur l'importance des systèmes de personnages (Woloch, 2003; Moretti, 2011). La méthode que nous utilisons pour construire le réseau est directe et simple. Nous extrayons les co-occurrences d'un index sans avoir recours à l'analyse textuelle. Nous décrivons les rôles narratifs des personnages en les déduisant de leurs positions relatives dans le réseau, donc du discours. Comme étude de cas, nous avons choisi le roman autobiographique Les Confessions, de Jean- Jacques Rousseau. Nous déduisons les co-occurrences entre personnages de l'index présent dans l'édition Slatkine (Rousseau et al., 2012). Sur le réseau obtenu, nous calculons quatre types de centralité : le degré, la proximité, l'intermédiarité et la centralité par vecteur propre. Nous utilisons ces mesures pour proposer une typologie des rôles narratifs des personnages. Nous montrons que les deux parties des Confessions, écrites à deux époques différentes, sont structurées autour de deux figures centrales, qui obtiennent des mesures de centralité similaires. La première partie est construite autour du mentor de Rousseau, qui a symbolisé une grande ouverture. La seconde partie se focalise sur un groupe de comploteurs, et retrace une période marquée par la paranoïa chez l'auteur. Nous mettons également en évidence des personnages jouant des rôles intermédiaires, et de fait procurant un lien narratif entre les différentes sociétés couvrant la vie de l'auteur. La méthode d'analyse des réseaux de personnages que nous décrivons peut être appliquée à tout texte de fiction comportant un index.

Evolutionary games on complex networks : the emergence and maintenance of cooperation

Abstract The object of game theory lies in the analysis of situations where different social actors have conflicting requirements and where their individual decisions will all influence the global outcome. In this framework, several games have been invented to capture the essence of various dilemmas encountered in many common important socio-economic situations. Even though these games often succeed in helping us understand human or animal behavior in interactive settings, some experiments have shown that people tend to cooperate with each other in situations for which classical game theory strongly recommends them to do the exact opposite. Several mechanisms have been invoked to try to explain the emergence of this unexpected cooperative attitude. Among them, repeated interaction, reputation, and belonging to a recognizable group have often been mentioned. However, the work of Nowak and May (1992) showed that the simple fact of arranging the players according to a spatial structure and only allowing them to interact with their immediate neighbors is sufficient to sustain a certain amount of cooperation even when the game is played anonymously and without repetition. Nowak and May's study and much of the following work was based on regular structures such as two-dimensional grids. Axelrod et al. (2002) showed that by randomizing the choice of neighbors, i.e. by actually giving up a strictly local geographical structure, cooperation can still emerge, provided that the interaction patterns remain stable in time. This is a first step towards a social network structure. However, following pioneering work by sociologists in the sixties such as that of Milgram (1967), in the last few years it has become apparent that many social and biological interaction networks, and even some technological networks, have particular, and partly unexpected, properties that set them apart from regular or random graphs. Among other things, they usually display broad degree distributions, and show small-world topological structure. Roughly speaking, a small-world graph is a network where any individual is relatively close, in terms of social ties, to any other individual, a property also found in random graphs but not in regular lattices. However, in contrast with random graphs, small-world networks also have a certain amount of local structure, as measured, for instance, by a quantity called the clustering coefficient. In the same vein, many real conflicting situations in economy and sociology are not well described neither by a fixed geographical position of the individuals in a regular lattice, nor by a random graph. Furthermore, it is a known fact that network structure can highly influence dynamical phenomena such as the way diseases spread across a population and ideas or information get transmitted. Therefore, in the last decade, research attention has naturally shifted from random and regular graphs towards better models of social interaction structures. The primary goal of this work is to discover whether or not the underlying graph structure of real social networks could give explanations as to why one finds higher levels of cooperation in populations of human beings or animals than what is prescribed by classical game theory. To meet this objective, I start by thoroughly studying a real scientific coauthorship network and showing how it differs from biological or technological networks using divers statistical measurements. Furthermore, I extract and describe its community structure taking into account the intensity of a collaboration. Finally, I investigate the temporal evolution of the network, from its inception to its state at the time of the study in 2006, suggesting also an effective view of it as opposed to a historical one. Thereafter, I combine evolutionary game theory with several network models along with the studied coauthorship network in order to highlight which specific network properties foster cooperation and shed some light on the various mechanisms responsible for the maintenance of this same cooperation. I point out the fact that, to resist defection, cooperators take advantage, whenever possible, of the degree-heterogeneity of social networks and their underlying community structure. Finally, I show that cooperation level and stability depend not only on the game played, but also on the evolutionary dynamic rules used and the individual payoff calculations. Synopsis Le but de la théorie des jeux réside dans l'analyse de situations dans lesquelles différents acteurs sociaux, avec des objectifs souvent conflictuels, doivent individuellement prendre des décisions qui influenceront toutes le résultat global. Dans ce cadre, plusieurs jeux ont été inventés afin de saisir l'essence de divers dilemmes rencontrés dans d'importantes situations socio-économiques. Bien que ces jeux nous permettent souvent de comprendre le comportement d'êtres humains ou d'animaux en interactions, des expériences ont montré que les individus ont parfois tendance à coopérer dans des situations pour lesquelles la théorie classique des jeux prescrit de faire le contraire. Plusieurs mécanismes ont été invoqués pour tenter d'expliquer l'émergence de ce comportement coopératif inattendu. Parmi ceux-ci, la répétition des interactions, la réputation ou encore l'appartenance à des groupes reconnaissables ont souvent été mentionnés. Toutefois, les travaux de Nowak et May (1992) ont montré que le simple fait de disposer les joueurs selon une structure spatiale en leur permettant d'interagir uniquement avec leurs voisins directs est suffisant pour maintenir un certain niveau de coopération même si le jeu est joué de manière anonyme et sans répétitions. L'étude de Nowak et May, ainsi qu'un nombre substantiel de travaux qui ont suivi, étaient basés sur des structures régulières telles que des grilles à deux dimensions. Axelrod et al. (2002) ont montré qu'en randomisant le choix des voisins, i.e. en abandonnant une localisation géographique stricte, la coopération peut malgré tout émerger, pour autant que les schémas d'interactions restent stables au cours du temps. Ceci est un premier pas en direction d'une structure de réseau social. Toutefois, suite aux travaux précurseurs de sociologues des années soixante, tels que ceux de Milgram (1967), il est devenu clair ces dernières années qu'une grande partie des réseaux d'interactions sociaux et biologiques, et même quelques réseaux technologiques, possèdent des propriétés particulières, et partiellement inattendues, qui les distinguent de graphes réguliers ou aléatoires. Entre autres, ils affichent en général une distribution du degré relativement large ainsi qu'une structure de "petit-monde". Grossièrement parlant, un graphe "petit-monde" est un réseau où tout individu se trouve relativement près de tout autre individu en termes de distance sociale, une propriété également présente dans les graphes aléatoires mais absente des grilles régulières. Par contre, les réseaux "petit-monde" ont, contrairement aux graphes aléatoires, une certaine structure de localité, mesurée par exemple par une quantité appelée le "coefficient de clustering". Dans le même esprit, plusieurs situations réelles de conflit en économie et sociologie ne sont pas bien décrites ni par des positions géographiquement fixes des individus en grilles régulières, ni par des graphes aléatoires. De plus, il est bien connu que la structure même d'un réseau peut passablement influencer des phénomènes dynamiques tels que la manière qu'a une maladie de se répandre à travers une population, ou encore la façon dont des idées ou une information s'y propagent. Ainsi, durant cette dernière décennie, l'attention de la recherche s'est tout naturellement déplacée des graphes aléatoires et réguliers vers de meilleurs modèles de structure d'interactions sociales. L'objectif principal de ce travail est de découvrir si la structure sous-jacente de graphe de vrais réseaux sociaux peut fournir des explications quant aux raisons pour lesquelles on trouve, chez certains groupes d'êtres humains ou d'animaux, des niveaux de coopération supérieurs à ce qui est prescrit par la théorie classique des jeux. Dans l'optique d'atteindre ce but, je commence par étudier un véritable réseau de collaborations scientifiques et, en utilisant diverses mesures statistiques, je mets en évidence la manière dont il diffère de réseaux biologiques ou technologiques. De plus, j'extrais et je décris sa structure de communautés en tenant compte de l'intensité d'une collaboration. Finalement, j'examine l'évolution temporelle du réseau depuis son origine jusqu'à son état en 2006, date à laquelle l'étude a été effectuée, en suggérant également une vue effective du réseau par opposition à une vue historique. Par la suite, je combine la théorie évolutionnaire des jeux avec des réseaux comprenant plusieurs modèles et le réseau de collaboration susmentionné, afin de déterminer les propriétés structurelles utiles à la promotion de la coopération et les mécanismes responsables du maintien de celle-ci. Je mets en évidence le fait que, pour ne pas succomber à la défection, les coopérateurs exploitent dans la mesure du possible l'hétérogénéité des réseaux sociaux en termes de degré ainsi que la structure de communautés sous-jacente de ces mêmes réseaux. Finalement, je montre que le niveau de coopération et sa stabilité dépendent non seulement du jeu joué, mais aussi des règles de la dynamique évolutionnaire utilisées et du calcul du bénéfice d'un individu.