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.

Brain network analysis of patients with Temporal Lobe Epilepsy

Patients with Temporal Lobe Epilepsy (TLE) suffer from widespread subtle white matter abnormalities and abnormal functional connectivity extending beyond the affected lobe, as revealed by Diffusion Tensor MR Imaging, volumetric and functional MRI studies. Diffusion Spectrum Imaging (DSI) is a diffusion imaging technique with high angular resolution for improving the mapping of white matter pathways. In this study, we used DSI, connectivity matrices and topological measures to investigate how the alteration in structural connectivity influences whole brain structural networks. Eleven patients with right-sided TLE and hippocampal sclerosis and 18 controls underwent our DSI protocol at 3T. The cortical and subcortical grey matters were parcellated into 86 regions of interest and the connectivity between every region pair was estimated using global tractography and a connectivity matrix (the adjacency matrix of the structural network). We then compared the networks of patients and controls using topological measures. In patients, we found a higher characteristic path length and a lower clustering coefficient compared to controls. Local measures at node level of the clustering and efficiency showed a significant difference after a multiple comparison correction (Bonferroni). These significant nodes were located within as well outside the temporal lobe, and the localisation of most of them was consistent with regions known to be part of epileptic networks in TLE. Our results show altered connectivity patterns that are concordant with the mapping of functional epileptic networks in patients with TLE. Further studies are needed to establish the relevance of these findings for the propagation of epileptic activity, cognitive deficits in medial TLE and outcome of epilepsy surgery in individual patients.

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.

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.

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.

The Role of Transnational Elites in shaping the evolving Field of Internet Governance

La gouvernance de l'Internet est une thématique récente dans la politique mondiale. Néanmoins, elle est devenue au fil des années un enjeu économique et politique important. La question a même pris une importance particulière au cours des derniers mois en devenant un sujet d'actualité récurrent. Forte de ce constat, c ette recherche retrace l'histoire de la gouvernance de l'Internet depuis son émergence comme enjeu politique dans les années 1980 jusqu'à la fin du Sommet Mondial sur la Société de l'Information (SMSI) en 2005. Plutôt que de se focaliser sur l'une ou l'autre des institutions impliquées dans la régulation du réseau informatique mondial, cette recherche analyse l'émergence et l'évolution historique d'un espace de luttes rassemblant un nombre croissant d'acteurs différents. Cette évolution est décrite à travers le prisme de la relation dialectique entre élites et non-élites et de la lutte autour de la définition de la gouvernance de l'Internet. Cette thèse explore donc la question de comment les relations au sein des élites de la gouvernance de l'Internet et entre ces élites et les non-élites expliquent l'emergence, l'évolution et la structuration d'un champ relativement autonome de la politique mondiale centré sur la gouvernance de l'Internet. Contre les perspectives dominantes réaliste et libérales, cette recherche s'ancre dans une approche issue de la combinaison des traditions hétérodoxes en économie politique internationale et des apports de la sociologie politique internationale. Celle-ci s'articule autour des concepts de champ, d'élites et d'hégémonie. Le concept de champ, développé par Bourdieu inspire un nombre croissant d'études de la politique mondiale. Il permet à la fois une étude différenciée de la mondialisation et l'émergence d'espaces de lutte et de domination au niveau transnational. La sociologie des élites, elle, permet une approche pragmatique et centrée sur les acteurs des questions de pouvoir dans la mondialisation. Cette recherche utilise plus particulièrement le concept d'élite du pouvoir de Wright Mills pour étudier l'unification d'élites a priori différentes autour de projets communs. Enfin, cette étude reprend le concept néo-gramscien d'hégémonie afin d'étudier à la fois la stabilité relative du pouvoir d'une élite garantie par la dimension consensuelle de la domination, et les germes de changement contenus dans tout ordre international. A travers l'étude des documents produits au cours de la période étudiée et en s'appuyant sur la création de bases de données sur les réseaux d'acteurs, cette étude s'intéresse aux débats qui ont suivi la commercialisation du réseau au début des années 1990 et aux négociations lors du SMSI. La première période a abouti à la création de l'Internet Corporation for Assigned Names and Numbers (ICANN) en 1998. Cette création est le résultat de la recherche d'un consensus entre les discours dominants des années 1990. C'est également le fruit d'une coalition entre intérêts au sein d'une élite du pouvoir de la gouvernance de l'Internet. Cependant, cette institutionnalisation de l'Internet autour de l'ICANN excluait un certain nombre d'acteurs et de discours qui ont depuis tenté de renverser cet ordre. Le SMSI a été le cadre de la remise en cause du mode de gouvernance de l'Internet par les États exclus du système, des universitaires et certaines ONG et organisations internationales. C'est pourquoi le SMSI constitue la seconde période historique étudiée dans cette thèse. La confrontation lors du SMSI a donné lieu à une reconfiguration de l'élite du pouvoir de la gouvernance de l'Internet ainsi qu'à une redéfinition des frontières du champ. Un nouveau projet hégémonique a vu le jour autour d'éléments discursifs tels que le multipartenariat et autour d'insitutions telles que le Forum sur la Gouvernance de l'Internet. Le succès relatif de ce projet a permis une stabilité insitutionnelle inédite depuis la fin du SMSI et une acceptation du discours des élites par un grand nombre d'acteurs du champ. Ce n'est que récemment que cet ordre a été remis en cause par les pouvoirs émergents dans la gouvernance de l'Internet. Cette thèse cherche à contribuer au débat scientifique sur trois plans. Sur le plan théorique, elle contribue à l'essor d'un dialogue entre approches d'économie politique mondiale et de sociologie politique internationale afin d'étudier à la fois les dynamiques structurelles liées au processus de mondialisation et les pratiques localisées des acteurs dans un domaine précis. Elle insiste notamment sur l'apport de les notions de champ et d'élite du pouvoir et sur leur compatibilité avec les anlayses néo-gramsciennes de l'hégémonie. Sur le plan méthodologique, ce dialogue se traduit par une utilisation de méthodes sociologiques telles que l'anlyse de réseaux d'acteurs et de déclarations pour compléter l'analyse qualitative de documents. Enfin, sur le plan empirique, cette recherche offre une perspective originale sur la gouvernance de l'Internet en insistant sur sa dimension historique, en démontrant la fragilité du concept de gouvernance multipartenaire (multistakeholder) et en se focalisant sur les rapports de pouvoir et les liens entre gouvernance de l'Internet et mondialisation. - Internet governance is a recent issue in global politics. However, it gradually became a major political and economic issue. It recently became even more important and now appears regularly in the news. Against this background, this research outlines the history of Internet governance from its emergence as a political issue in the 1980s to the end of the World Summit on the Information Society (WSIS) in 2005. Rather than focusing on one or the other institution involved in Internet governance, this research analyses the emergence and historical evolution of a space of struggle affecting a growing number of different actors. This evolution is described through the analysis of the dialectical relation between elites and non-elites and through the struggle around the definition of Internet governance. The thesis explores the question of how the relations among the elites of Internet governance and between these elites and non-elites explain the emergence, the evolution, and the structuration of a relatively autonomous field of world politics centred around Internet governance. Against dominant realist and liberal perspectives, this research draws upon a cross-fertilisation of heterodox international political economy and international political sociology. This approach focuses on concepts such as field, elites and hegemony. The concept of field, as developed by Bourdieu, is increasingly used in International Relations to build a differentiated analysis of globalisation and to describe the emergence of transnational spaces of struggle and domination. Elite sociology allows for a pragmatic actor-centred analysis of the issue of power in the globalisation process. This research particularly draws on Wright Mill's concept of power elite in order to explore the unification of different elites around shared projects. Finally, this thesis uses the Neo-Gramscian concept of hegemony in order to study both the consensual dimension of domination and the prospect of change contained in any international order. Through the analysis of the documents produced within the analysed period, and through the creation of databases of networks of actors, this research focuses on the debates that followed the commercialisation of the Internet throughout the 1990s and during the WSIS. The first time period led to the creation of the Internet Corporation for Assigned Names and Numbers (ICANN) in 1998. This creation resulted from the consensus-building between the dominant discourses of the time. It also resulted from the coalition of interests among an emerging power elite. However, this institutionalisation of Internet governance around the ICANN excluded a number of actors and discourses that resisted this mode of governance. The WSIS became the institutional framework within which the governance system was questioned by some excluded states, scholars, NGOs and intergovernmental organisations. The confrontation between the power elite and counter-elites during the WSIS triggered a reconfiguration of the power elite as well as a re-definition of the boundaries of the field. A new hegemonic project emerged around discursive elements such as the idea of multistakeholderism and institutional elements such as the Internet Governance Forum. The relative success of the hegemonic project allowed for a certain stability within the field and an acceptance by most non-elites of the new order. It is only recently that this order began to be questioned by the emerging powers of Internet governance. This research provides three main contributions to the scientific debate. On the theoretical level, it contributes to the emergence of a dialogue between International Political Economy and International Political Sociology perspectives in order to analyse both the structural trends of the globalisation process and the located practices of actors in a given issue-area. It notably stresses the contribution of concepts such as field and power elite and their compatibility with a Neo-Gramscian framework to analyse hegemony. On the methodological level, this perspective relies on the use of mixed methods, combining qualitative content analysis with social network analysis of actors and statements. Finally, on the empirical level, this research provides an original perspective on Internet governance. It stresses the historical dimension of current Internet governance arrangements. It also criticise the notion of multistakeholde ism and focuses instead on the power dynamics and the relation between Internet governance and globalisation.

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.

Structural Analysis of Networks

Network analysis naturally relies on graph theory and, more particularly, on the use of node and edge metrics to identify the salient properties in graphs. When building visual maps of networks, these metrics are turned into useful visual cues or are used interactively to filter out parts of a graph while querying it, for instance. Over the years, analysts from different application domains have designed metrics to serve specific needs. Network science is an inherently cross-disciplinary field, which leads to the publication of metrics with similar goals; different names and descriptions of their analytics often mask the similarity between two metrics that originated in different fields. Here, we study a set of graph metrics and compare their relative values and behaviors in an effort to survey their potential contributions to the spatial analysis of networks.

Validation of network communicability metrics for the analysis of brain structural networks.

Computational network analysis provides new methods to analyze the brain's structural organization based on diffusion imaging tractography data. Networks are characterized by global and local metrics that have recently given promising insights into diagnosis and the further understanding of psychiatric and neurologic disorders. Most of these metrics are based on the idea that information in a network flows along the shortest paths. In contrast to this notion, communicability is a broader measure of connectivity which assumes that information could flow along all possible paths between two nodes. In our work, the features of network metrics related to communicability were explored for the first time in the healthy structural brain network. In addition, the sensitivity of such metrics was analysed using simulated lesions to specific nodes and network connections. Results showed advantages of communicability over conventional metrics in detecting densely connected nodes as well as subsets of nodes vulnerable to lesions. In addition, communicability centrality was shown to be widely affected by the lesions and the changes were negatively correlated with the distance from lesion site. In summary, our analysis suggests that communicability metrics that may provide an insight into the integrative properties of the structural brain network and that these metrics may be useful for the analysis of brain networks in the presence of lesions. Nevertheless, the interpretation of communicability is not straightforward; hence these metrics should be used as a supplement to the more standard connectivity network metrics.

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.

ConnectomeViewer - Multi-Modal Multi-Level Network Visualization and Analysis.

Introduction: The field of Connectomic research is growing rapidly, resulting from methodological advances in structural neuroimaging on many spatial scales. Especially progress in Diffusion MRI data acquisition and processing made available macroscopic structural connectivity maps in vivo through Connectome Mapping Pipelines (Hagmann et al, 2008) into so-called Connectomes (Hagmann 2005, Sporns et al, 2005). They exhibit both spatial and topological information that constrain functional imaging studies and are relevant in their interpretation. The need for a special-purpose software tool for both clinical researchers and neuroscientists to support investigations of such connectome data has grown. Methods: We developed the ConnectomeViewer, a powerful, extensible software tool for visualization and analysis in connectomic research. It uses the novel defined container-like Connectome File Format, specifying networks (GraphML), surfaces (Gifti), volumes (Nifti), track data (TrackVis) and metadata. Usage of Python as programming language allows it to by cross-platform and have access to a multitude of scientific libraries. Results: Using a flexible plugin architecture, it is possible to enhance functionality for specific purposes easily. Following features are already implemented: * Ready usage of libraries, e.g. for complex network analysis (NetworkX) and data plotting (Matplotlib). More brain connectivity measures will be implemented in a future release (Rubinov et al, 2009). * 3D View of networks with node positioning based on corresponding ROI surface patch. Other layouts possible. * Picking functionality to select nodes, select edges, get more node information (ConnectomeWiki), toggle surface representations * Interactive thresholding and modality selection of edge properties using filters * Arbitrary metadata can be stored for networks, thereby allowing e.g. group-based analysis or meta-analysis. * Python Shell for scripting. Application data is exposed and can be modified or used for further post-processing. * Visualization pipelines using filters and modules can be composed with Mayavi (Ramachandran et al, 2008). * Interface to TrackVis to visualize track data. Selected nodes are converted to ROIs for fiber filtering The Connectome Mapping Pipeline (Hagmann et al, 2008) processed 20 healthy subjects into an average Connectome dataset. The Figures show the ConnectomeViewer user interface using this dataset. Connections are shown that occur in all 20 subjects. The dataset is freely available from the homepage (connectomeviewer.org). Conclusions: The ConnectomeViewer is a cross-platform, open-source software tool that provides extensive visualization and analysis capabilities for connectomic research. It has a modular architecture, integrates relevant datatypes and is completely scriptable. Visit www.connectomics.org to get involved as user or developer.

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.