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Purpose/Aim: To find power structures within the blog network. Material/Method: Using keywords to find all available blog posts about the National Defence Radio Establishment from the blog search engine Twingly, and thereafter using the same blog search engine to find inlinks from other blogs, to those posts. The data is set into the context of the small-world networks models of Duncan J. Watts and rich-club models of Sergi Valverde och Ricard V. Sole. Main results: 5183 unique blogs have written about the subject in 22779 blog posts to which 28128 inlinks from other blogposts are made. Just over one fifth of the blogs are linkted to each other in one big network, where the remaining blogs stand without any ingoing or outgoing links. The first bloggers are the one who continue to write for longer period of time and also the ones who attracts most inlinks. The blogosphere around this subject is highly connected, shows features as one would find in a small-world network, displays a power-law distribution for inlinks and is highly clustered around a few rich- club nodes.

Networks are all around us, all the time. From the biochemistry of our cells to the web of friendships across the planet. From the circuitry of modern electronics to chains of historical events. A network is the result of the forces that shaped it. Thus the principles of network formation can be, to some extent, deciphered from the network itself. All such information comprises the structure of the network. The study of network structure is the core of modern network science. This thesis centres around three aspects of network structure: What kinds of network structures are there and how can they be measured? How can we build models for network formation that give the structure of networks in the real world? How does the network structure affect dynamical systems confined to the networks? These questions are discussed using a variety of statistical, analytical and modelling techniques developed by physicists, mathematicians, biologists, chemists, psychologists, sociologists and anthropologists. My own research touches all three questions. In this thesis I present works trying to answer: What is the best way to protect a network against sinister attacks? How do groups form in friendship networks? Where do traffic jams appear in a communication network? How is cellular metabolism organised? How do Swedes flirt on the Internet? . . . and many other questions.

Software engineering projects that utilize inappropriate pathfinding algorithms carry a significant risk of poor runtime performance for customers. Using social network theory, this experimental study examined the impact of algorithms, frameworks, and map complexity on elapsed time and computer memory consumption. The 1,800 2D map samples utilized were computer random generated and data were collected and processed using Python language scripts. Memory consumption and elapsed time results for each of the 12 experimental treatment groups were compared using factorial MANOVA to determine the impact of the 3 independent variables on elapsed time and computer memory consumption. The MANOVA indicated a significant factor interaction between algorithms, frameworks, and map complexity upon elapsed time and memory consumption, F(4, 3576) = 94.09, p < .001, h2 = .095. The main effects of algorithms, F(4, 3576) = 885.68, p < .001, h2 = .498; and frameworks, F(2, 1787) = 720,360.01, p .001, h2 = .999; and map complexity, F(2, 1787) = 112,736.40, p < .001, h2 = .992, were also all significant. This study may contribute to positive social change by providing software engineers writing software for complex networks, such as analyzing terrorist social networks, with empirical pathfinding algorithm results. This is crucial to enabling selection of appropriately fast, memory-efficient algorithms that help analysts identify and apprehend criminal and terrorist suspects in complex networks before the next attack.

Le sujet principal de la thèse sont les systèmes de particules en interaction sur des graphes soit deterministes soit aléatoires. Les systèmes de particules en interaction sont des processus de Markov qui décrivent l'évolution de particules indistingables en interaction forte les unes avec les autres qui sont utilisés pour modéliser des phénomènes d'épidémies, de dynamiques des populations ou des processus chimiques. Dans la première partie de la thèse nous avons analysé l'ordre stochastique et l'attractivité dans une classe de systèmes de particules avec des naissances, des morts et des sauts de plus d'une particule à la fois qui dépendent de la conguration de manière très générale: nous avons utilisé l'attractivité pour obtenir des resultats d'ergodicité pour des modèles d'epidemie et pour construire des mesures invariantes non-triviales pour des modèles de dinamiques de métapopulations. Dans la deuxième partie de la thèse nous avons analysé les marches aléatoires coalescentes sur des graphes aléatoires, les graphes small world. Nous avons montré que le nombre de particules d'un processus de n marches aléatoires coalescentes renormalisées qui partent d'une ensemble particulier sur le small world converge vers un processus coalescent de Kingman. Nous avons aussi obtenu des resultats detaillés sur le temps de rencontre de deux particules sur le small world.

<p>Networks are all around us, all the time. From the biochemistry of our cells to the web of friendships across the planet. From the circuitry of modern electronics to chains of historical events. A network is the result of the forces that shaped it. Thus the principles of network formation can be, to some extent, deciphered from the network itself. All such information comprises the structure of the network. The study of network structure is the core of modern network science. This thesis centres around three aspects of network structure: What kinds of network structures are there and how can they be measured? How can we build models for network formation that give the structure of networks in the real world? How does the network structure affect dynamical systems confined to the networks? These questions are discussed using a variety of statistical, analytical and modelling techniques developed by physicists, mathematicians, biologists, chemists, psychologists, sociologists and anthropologists. My own research touches all three questions. In this thesis I present works trying to answer: What is the best way to protect a network against sinister attacks? How do groups form in friendship networks? Where do traffic jams appear in a communication network? How is cellular metabolism organised? How do Swedes flirt on the Internet? . . . and many other questions.</p>

This thesis examines the urban morphology of fifty cities using spatial syntax analysis. The analysis compares the urban street networks of European, USA, Islamic and East Asian cities. Street connectivity was the main metric and natural roads were the basis for the analysis. The aim of the study was to analyze determine how sensitive space syntax methods are for uncovering the hierarchical patterns of urban street networks and examining their scale-free and small-world properties. Street data was collected from OpenStreetMap. ArcGIS 10 with the Axwoman extension was used to study the hierarchical levels of street networks. Matlab provided the platform to examine the scale-free property of street data. Pajek software was used to measure the small-world behavior. Based on the hierarchical representation, the fifty sample cities were classified into different groups and their scale-free and small-world properties were studied. From a traditionally morphological perspective, it was found that some cities in Europe have a close-knit cellular and organic urban morphology. Cities in the USA exhibit gridiron patterns on the whole. Some Islamic cities have special urban structure with houses grouped around the cul-de-sac lanes. Several of the East Asian cities studied also have grid forms. According to the space syntax analysis, urban street networks that have a connectivity value greater than the average value were less than 40%. The results showed that for most cities, the street connectivity distribution follows a power-law distribution and exhibits scale-free properties. Urban street networks of all sample cities were found to have a small-world property. Space syntax cannot detect all of the morphological patterns recognized in traditional morphological studies. The method can, however, efficiently quantify the spatial configuration of a large sample. Space syntax’s topological and scaling metrics thus provide a way to compare urban street networks. These metrics can thus help classify cities according to their street patterns but also contribute to an understanding of human behavior within and thus the design of urban spaces. For example, an urban street network with a small-world property could have high efficiency for traffic flows at local and global levels and should be considered in further study.

Este trabalho explora o uso da Análise de Redes Sociais (ARS) como ferramenta de grande valor, aquela que perpassa pelas mais variadas disciplinas, como protagonista do estudo em alguns casos, como coadjuvante em outros. Para a Ciência da Informação, a ARS vem sendo empregada em estudos bibliométricos, procurando responder a questionamentos que intrigam pesquisadores da área ou de outros segmentos do conhecimento. Assim, a ARS ocupa seu espaço como o objeto principal dos estudos, enfatizando-a como ferramenta e, também, pelo seu uso direto em pesquisas nas quais aparece, frequentemente em conjunto com a estatística. Dessa forma, a ARS é empregada, pensando em Ciência da Informação, em ambos os papéis: como protagonista, nas frentes que abordam sua história, seus métodos e suas métricas, e, como coadjuvante, contribuindo na análise de redes de coautoria através de suas métricas de centralidade, mostrando a fluência das informações, determinando a posição de autores com relação à colaboração e seus comportamentos em rede para áreas como a Ciência da Informação, a Educação e a Sociologia. Os gráficos e tabelas foram elaborados com o apoio dos programas Microsoft Excel e, fundamentalmente para as redes de interesse, o programa de uso livre Pajek. Este último, alimentado por programas em VBScript, possibilitou, através de seus recursos de geração de imagens representativas das redes, a confecção dos gráficos e o cálculo dos indicadores para cada uma das três redes. Para a obtenção dos dados de entrada, foram utilizados os mecanismos de busca pela expressão \"Social Networks\" nas bases ASSIA (Sociologia), ERIC (Educação) e LISA (Ciência da Informação) e, com o uso de seus mecanismos internos, a massa foi exportada e empregada como exemplo de bases viabilizando a aplicação e verificação da metodologia proposta nos moldes dos estudos realizados. / This dissertation explores the use of Social Network Analysis (SNA) as a valuable tool, which runs through the most varied disciplines, as a protagonist in same study cases, as an adjunct in other cases. For the Information Science, the SNA has been used in bibliometric studies, trying to answer questions that intrigue researchers in this field or other segments of knowledge. So, the SNA occupies its place as the main object of the studies, emphasizing it as a tool and also for its direct use in researches in which it appears, often in conjunction with the statistics. Thus, the SNA is used, concerning the Information Science, in both roles: as the protagonist, foremost addressing its history, its methods and metrics, and, as an adjunct, contributing for the analysis of networks of co-authorship through its centrality metrics, showing the flow of information, determining the position of the authors, related to their collaboration and their behaviors on the network, for areas of study such as Information Science, Education and Sociology. The graphs and charts were elaborated with the support of Microsoft Excel program and, fundamentally to the networks of interest, the program of free use called Pajek. The latter, powered by VBScript programs, enabled, through its resources of generating representative network images, the elaboration of the graphs and the calculation of the indicators for each one of the three networks. To obtain the input data, search engines were used by the expression \"Social Networks\" in ASSIA (Sociology), ERIC (Education) and LISA (Information Science) bases and, using its internal mechanisms, the mass was exported and used as an example of bases enabling the application and verification of the proposed methodology along the lines of the studies.

People relate with one another in space and through imagined and technologically mediated networks. This thesis is concerned with the relationship between these two types of social connections – spatial and network. Spatial connections structure collectives of people in the same place at the same time. Network connections structure relations between people without regard to place or time. Spatial connections are complex, but rigid by nature, while network connections are simple, but flexible. Essential articulations emerge between these two connection types. These articulations create and evolve contemporary socio-spatial systems such as the city, its many places, and groups of people therein. However, the basic human experience of these systems remains largely polarized between spatial and network social practices to the disadvantage of human agency. This thesis proposes a teleodynamic, socio-spatial interaction model for the articulation of these social practices in human agency architecture. The model is a mobile experience design that functions through people with ‘smart’ mobile devices. It connects them with one another in public place and to global information and communication networks simultaneously. Sociological study informs the model’s design – constraints and conditions for the connection extents and integrity of social interaction. The model supports self-organizing circular relationships between human interaction dynamics and their trace structures based on a methodology for emergence in complex systems. It effects the emergence of the aforementioned socio-spatial, human agency architecture, with great flexibility. The model and architecture together serve to better articulate contemporary spatial and network social practices to the benefit of human agency in urban space.

People relate with one another in space and through imagined and technologically mediated networks. This thesis is concerned with the relationship between these two types of social connections – spatial and network. Spatial connections structure collectives of people in the same place at the same time. Network connections structure relations between people without regard to place or time. Spatial connections are complex, but rigid by nature, while network connections are simple, but flexible. Essential articulations emerge between these two connection types. These articulations create and evolve contemporary socio-spatial systems such as the city, its many places, and groups of people therein. However, the basic human experience of these systems remains largely polarized between spatial and network social practices to the disadvantage of human agency. This thesis proposes a teleodynamic, socio-spatial interaction model for the articulation of these social practices in human agency architecture. The model is a mobile experience design that functions through people with ‘smart’ mobile devices. It connects them with one another in public place and to global information and communication networks simultaneously. Sociological study informs the model’s design – constraints and conditions for the connection extents and integrity of social interaction. The model supports self-organizing circular relationships between human interaction dynamics and their trace structures based on a methodology for emergence in complex systems. It effects the emergence of the aforementioned socio-spatial, human agency architecture, with great flexibility. The model and architecture together serve to better articulate contemporary spatial and network social practices to the benefit of human agency in urban space.