Ce travail de thèse vise à comprendre les dynamiques sociales qui viennent influencer le processus d’appropriation d’une technologie SNA au sein d’une organisation. Pour ce faire, nous avons mené une étude inter-cas menée au sein de deux collectivités territoriales françaises et une étude intra-cas chez BOUYGUES CONSTRUCTION en nous appuyant sur un cadre théorique mobilisant la théorie de l’acteur stratégique de Crozier et Friedberg et la théorie de la pratique de Bourdieu. Un des principaux résultats de cette thèse est que l’appropriation d’une technologie SNA passe principalement par une appropriation socio-politique en deux phases : une phase d’appropriation de la nouvelle dimension donnée au capital social et une phase d’appropriation de la technologie pour servir les intérêts des acteurs concernant le développement du capital social. Nous avons également identifié que l’introduction d’un outil SNA est assignée à différentes notions symboliques (symbole de la légitimité du contrôle et de la supervision, symbole du soutien du top-management des pratiques de travail transversales, le symbole de la rigidité des structures organisationnelles, le symbole de la gestion des ressources informelles comme une ressource spécifique, le symbole de l’exclusion…) qui viennent légitimer et asseoir les différentes stratégies des groupes d’acteurs. Enfin, nous avons constaté que certains symboles liés à l’introduction du SNA sont étroitement liés à la culture de l’organisation. Ces principaux résultats ont pu être confortés par l’étude intra-cas menée chez BOUYGUES CONSTRUCTION, présentée comme une étude d’un cas particulier pouvant complémenter l’investigation menée au sein des deux collectivités territoriales. / This thesis aims to understand the social dynamics that influences actors’ adoption of a SNA tool in an organization. We have conducted multiple-case studies of two French Administrations (Mayoral offices) and an additional single case referred to a French industry BOUYGUES CONSTRUCTION drawing on Crozier and Friedberg’s theory of strategic actor and Bourdieu’s theory of practice. The first principle result is that the adoption of a SNA technology is primarily a socio-political appropriation that occurs through two phases: in the first phase actors discover social capital as a new symbolic capital and in a second phase they use the technology to influence the development of the organizational social capital in order it can serve their own interests. We have also identified that the introduction of a SNAS tool is assigned to different symbolic notions (symbol of the legitimization for control and supervision, symbol of top-management support for the development of transversal work practices, symbol of the rigidity of organizational structure, symbol of the management of informal resource as specific resource, symbol of exclusion) useful to provide legitimacy to the actors’ strategies in organizations. Finally, we highlight that these symbolic notions appear connected to the organizational culture. These key findings have emerged from our multiple-case study and have been reinforced the additional single case studied in BOUYGUES CONSTRUCTION. This single case complements the investigation conducted in the two Mayoral offices.

La notion de communauté, transverse à  l'analyse des réseaux sociaux, a attiré une attention grandissante à  travers les sciences ces dix dernières années. Les nombreuses tentatives pour modéliser aussi bien l'incarnation sociologiquedu concept aussi bien que sa manifestation structurelle dans le réseau social n'ont jusqu'à  présent que vaguement convergé. Aucun consensus formel n'a été atteint sur les aspects quantifiables de la communauté, et ceci malgré lesliens forts la reliant aux dimensions dynamique et topologique du réseau sous-jacent.Présentant une approche novatrice à  l'évaluation des communautés, cette thèse introduit et se base sur la cohésion, une métrique qui capture la qualitéintrinsèque, en tant que communauté, d'un ensemble de sommets dans un réseau. Il a été montré au travers d'une experience à  large échelle, dans laquelle les individus sondés ont pu noter l'aspect communautaires de groupes d'amis leur étant présentés, que la cohésion, définie en lien avec la notion de triades sociales, est fortement correlée à  la perception subjective de la communauté. Reflétant la complexité des interactions sociales, il est démontré que leproblème de trouver des communautés maximalement cohésive est NP-dur. En utilisant une heuristique approximant les résultats de ce problème, un certain nombre d'applications de la cohésion à  des données réelles sont mises en avant: de son application à  la visualisation de réseaux complexes, à  l'étude de l'évolution des groupes d'agrément du sénat états-unien, à  la compréhesion des liens entre psychologie et structure du réseau social.L'utilisation de la cohésion apporte un éclairage non trivial dans l'étude de la structure des grands réseaux de terrain et dans la relation entre structure et sémantique. / Community, a notion transversal to all areas of Social Network Analysis, has drawn tremendous amount of attention across the sciences in the past decades. Numerous attempts to characterize both the sociological embodiment of the concept as well as its observable structural manifestation in the social network have to this date only converged in spirit. No formal consensus has been reached on the quantifiable aspects of community, despite it being deeply linked to topological and dynamic aspects of the underlying social network. Presenting a fresh approach to the evaluation of communities, this thesis introduces and builds upon the cohesion, a novel metric which captures the intrinsic quality, as a community, of a set of nodes in a network. The cohesion, defined in terms of social triads, was found to be highly correlated to the subjective perception of communitiness through the use of a large-scale online experiment in which users were able to compute and rate the quality of their social groups on Facebook. Adequately reflecting the complexity of social interactions, the problem of finding a maximally cohesive group inside a given social network is shown to be NP-hard. Using a heuristic approximation algorithm, applications of the cohesion to broadly different use cases are highlighted, ranging from its application to network visualization, to the study of the evolution of agreement groups in the United States Senate, to the understanding of the intertwinement between subjects' psychological traits and the cohesive structures in their social neighborhood. The use of the cohesion proves invaluable in that it offers non-trivial insights on the network structure and its relation to the associated semantic.

Com o aumento dos usuários acessando a internet no Brasil, cresce a quantidade de conteúdo produzido por brasileiros. Assim se torna importante classificar os melhores autores para que se tenha mais confiança nos textos lidos. Nesse sentido, esta dissertação faz um estudo sobre a descoberta de autoridades em tópicos na blogosfera brasileira. O escopo de estudo e análise é a plataforma de publicação de blogs, Blogspot, sobre os blogueiros que se identificam como brasileiros. Para tanto, foram coletados nove milhões de postagens do ano de 2012 e considerados os comentários como fonte de relacionamento entre os blogueiros para gerar uma rede social. Essa rede foi usada para experimentos do algoritmo de identificação de autoridades em tópicos. O algoritmo utilizado como base é o Topic PageRank, separando os diversos tópicos da blogosfera pelas tags que os usuários definem em suas postagens e posteriormente construindo a lista das autoridades em tais tópicos. Experimentos realizados demonstram que o método proposto resulta em melhor ranqueamento que o algoritmo original do PageRank. Cabe salientar que foi feita uma caracterização dos dados coletados por um questionário aplicado a quatro mil autores. / With the intesification of users accessing the Internet in Brazil, the amount of content produced by Brazilians increases. Thus, it becomes important to classify the best authors to have more confidence in the texts read. In this sense, this work presents a study on subject of topic authorities discovery in the Brazilian blogosphere. The scope of the study is the Blogspot platform, focusing on bloggers who identify themselves as Brazilians. To this end, we collected nine millions posts in the year of 2012 and considered the comments as a source of relationship between bloggers to generate a social network. This network was used for performing experiments considering the proposed approach to identify topic authorities. The algorithm used is based on the Topic PageRank, which can separate the different blogosphere’s topics by tags that users use on their posts, and then building the list of authorities on such topics. The experiments conducted show that the proposed approach results in better ranking than the original PageRank algorithm. We also characterize the collected database with a survey of over four thousand authors.

Internet tem sido uma importante fonte para as pessoas que buscam informações de saúde. Isto é particularmente problemático na perspectiva da Web 2.0. A Web 2.0 é a segunda geração da World Wide Web, onde os usuários interagem e colaboram uns com os outros como criadores de conteúdo. A falta de qualidade das informações médicas na Web 2.0 tem suscitado preocupações com os impactos prejudiciais que podem acarretar. São muitos os aspectos relacionados à qualidade da informação que devem ser investigados, como por exemplo, existe alguma evidência de que o autor tem alguma autoridade no domínio da saúde? Há indícios de que os autores são tendenciosos? Como saber se a fonte de informação tem reputação, como separar as fontes de boa qualidade das outras? Esses questionamentos se tornam mais evidentes quando se faz buscas no Twitter. O usuário precisa por si só selecionar o conteúdo que acredita que tenha qualidade entre as centenas de resultados. Nesse contexto, o principal objetivo deste trabalho é propor e avaliar uma abordagem que permita estimar a reputação de fontes de informação no domínio da saúde. Acredita-se que discussões sobre reputação só fazem sentido quando possuem um propósito e estão inseridas em um contexto. Sendo assim, considera-se que reputação é um atributo que um usuário se apropria quando a informação que ele divulga é crível e digna de confiança. As contribuições desta tese incluem uma nova metodologia para estimar a reputação e uma estrutura topológica de rede baseada no grau de interação entre atores sociais. O estudo permitiu compreender como as métricas afetam o ordenamento da reputação. Escolher a métrica mais apropriada depende basicamente daquilo que se quer representar. No nosso caso, o Pagerank funcionou como um “contador de arcos” representando apenas uma medida de popularidade daquele nó. Verificou-se que popularidade (ou uma posição de destaque na rede) não necessariamente se traduz em reputação no domínio médico. Os resultados obtidos evidenciaram que a metodologia de ordenamento e a topologia da rede obtiveram sucesso em estimar a reputação. Além disso, foi verificado que o ambiente Twitter desempenha um papel importante na transmissão da informação e a “cultura” de encaminhar uma mensagem permitiu inferir processos de credibilidade e consequentemente a reputação. / The Internet is an important source for people who are seeking healthcare information. This is particularly problematic in era of Web 2.0. The Web 2.0 is a second generation of World Wide Web, where users interact and collaborate with each other as creators of content. Many concerns have arisen about the poor quality of health-care information on the Web 2.0, and the possibility that it leads to detrimental effects. There are many issues related to information quality that users continuously have to ask, for example, is there any evidence that the author has some authority in health domain? Are there clues that the authors are biased? How shall we know what our sources are worth, how shall we be able to separate the bad sources from the good ones? These questions become more obvious when searching for content in Twitter. The user then needs to manually pick out high quality content among potentially thousands of results. In this context, the main goal of this work is to propose an approach to infer the reputation of source information in the medical domain. We take into account that, discussion of reputation is usually not meaningful without a specific purpose and context. Thus, reputation is an attribute that a user comprises, and the information disseminated by him is credible and worthy of belief. Our contributions were to provide a new methodology to Rank Reputation and a new network topological structure based on weighted social interaction. The study gives us a clear understanding of how measures can affect the reputation rank. Choosing the most appropriate measure depends on what we want to represent. In our case, the PageRank operates look alike “edges counts” as the “popularity” measures. We noticed that popularity (or key position in a graph) does not necessarily refer to reputation in medical domain. The results shown that our rank methodology and the network topology have succeeded in achieving user reputation. Additionally, we verified that in Twitter community, trust plays an important role in spreading information; the culture of “retweeting” allowed us to infer trust and consequently reputation.

Submitted by Fabio Sobreira Campos da Costa (fabio.sobreira@ufpe.br) on 2016-06-29T12:16:01Z No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Dissertação - vbc.pdf: 3425848 bytes, checksum: 8e244d83612f4d849475c13a6af455d4 (MD5) / Made available in DSpace on 2016-06-29T12:16:01Z (GMT). No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Dissertação - vbc.pdf: 3425848 bytes, checksum: 8e244d83612f4d849475c13a6af455d4 (MD5) Previous issue date: 2014-09-01 / A aplicação de Análise de Redes Sociais (SNA – Social Network Analysis) em times de projetos de software tem sido um tópico de pesquisa bastante explorado e usado na última década. A fim de entender as relações entre pessoas, grupos, organizações ou outros tipos de entidades sociais, por meio de grafos e métricas próprias, SNA aparece como uma alternativa para expandir a visão da dinâmica de projetos no campo das relações sociais. Visualizando um projeto representado por um grafo, as entidades sociais são representadas como nós e suas relações como arestas, e análises temporais e/ou atemporais sobre aspectos de projetos, como comunicação, formação de equipe, colaboração, entre outros, podem ser realizadas usando métricas próprias como por exemplo betweenness centrality e densidade. O tipo de projeto mais estudado por pesquisadores que usam Análise de Redes Sociais é o projeto de desenvolvimento de software open source (OSS – Open Source Software). Pela facilidade na obtenção dos dados, armazenados em repositórios online, esta categoria de projeto tem levantado a curiosidade da comunidade acadêmica a fim de investigar suas características. OSS se distingue dos projetos tradicionais (chamados de closed source) pois envolve a participação de vários integrantes de forma espontânea, geralmente de localidade distintas e que nunca tiveram um contato pessoal entre si. Tendo em vista a extensão, em quantidade, de pesquisas que combinam o uso de técnicas de SNA em projetos OSS, esta dissertação tem como objetivo, através de um mapeamento sistemático da literatura, mapear e categorizar estudos diretamente relacionados à análise de redes sociais em projetos de software open source. Por meio de estatística descritiva e análise qualitativa busca-se conhecer quais os principais benefícios e limitações encontrados na aplicação das métricas de análise de redes sociais nos projetos de software OSS, bem como os principais tópicos de pesquisa e fontes de dados utilizadas. O trabalho, em sua síntese, apresenta um diagnóstico da pesquisa atual sobre os temas abordados e colabora com a academia apontando tendências e trabalhos futuros. / The application of Social Network Analysis (SNA) in teams of software projects has been a well researched and used topic in the last decade. In order to understand the relation between people, groups, organizations and other social entities, by the use of its own graphs and metrics, SNA appears to be an alternative to expand the vision of the projects dynamics in the social relation field. Seeing a project represented in a graph, the social entities are represented as dots and its relations as edges, and the temporal and/or timeless analysis about the projects aspects, such as communication, team building, coworking and others, can be performed by the use of own metrics, e.g. betweenness centrality and density. The kind of project most studied by researchers that use Social Network Analysis is the open source (OSS – Open Source Software) software development. This project category has been raising the academic community curiosity to investigate its characteristics since it is easy to obtain the data, stored in online repositories. OSS distinguishes from traditional projects (called closed source) because involves the participation of many spontaneous member, usually from different location and that have never met. As there are many researches that combine the use of SNA techniques in OSS projects, this thesis has the purpose to map and categorize, through a systematic mapping of the literature, studies directly related to the analysis of social network in open source software projects. Using descriptive statistics and qualitative analysis, seeks the main benefits and limitations found on the application of social network analysis metrics in the OSS software projects, as well as the main research topics and the used data source. To sum up, this dissertation presents a diagnose of the research about the covered topics and collaborates with the academy pointing tendencies and future work.

As of late there has been an immense increase of data within modern society. This is evident within the field of telecommunications. The amount of mobile data is growing fast. For a telecommunication operator, this provides means of getting more information of specific subscribers. The applications of this are many, such as segmentation for marketing purposes or detection of churners, people about to switching operator. Thus the analysis and information extraction is of great value. An approach of this analysis is that of social network analysis. Utilizing such methods yields ways of finding the importance of each individual subscriber in the network. This thesis aims at investigating the usefulness of social network analysis in telecommunication networks. As these networks can be very large the methods used to study them must scale linearly when the network size increases. Thus, an integral part of the study is to determine which social network analysis algorithms that have this scalability. Moreover, comparisons of software solutions are performed to find product suitable for these specific tasks. Another important part of using social network analysis is to be able to interpret the results. This can be cumbersome without expert knowledge. For that reason, a complete process flow for finding influential subscribers in a telecommunication network has been developed. The flow uses input easily available to the telecommunication operator. In addition to using social network analysis, machine learning is employed to uncover what behavior is associated with influence and pinpointing subscribers behaving accordingly.

Le principal objectif de cette thèse est d'évaluer les protocoles qui prennent en considération la protection de la vie privée et qui nécessitent seulement des métadonnées locales pour détecter les comportements malveillants sur les réseaux sociaux décentralisés. En appliquant des techniques d'analyse de réseaux sociaux qui réduisent la quantité de métadonnées sensibles, nous obtenons des résultats acceptables comparé aux techniques qui ne préservent pas la vie privée. De plus, nous prévoyons d'élaborer une série de recommandations pour construire de futurs réseaux sociaux décentralisés qui découragent cette type des comportements abusifs. / The main goal of this thesis is to evaluate privacy-preserving protocols to detect abuse in future decentralised online social platforms or microblogging services, where often limited amount of metadata is available to perform data analytics. Taking into account such data minimization, we obtain acceptable results compared to techniques of machine learning that use all metadata available. We draw a series of conclusion and recommendations that will aid in the design and development of a privacy-preserving decentralised social network that discourages abusive behavior.

How do local homeland security organizations respond to catastrophic events such as hurricanes and acts of terrorism? Among the most important aspects of this response are these organizations ability to adapt to the uncertain nature of these “focusing events” (Birkland 1997). They are often behind the curve, seeing response as a linear process, when in fact it is a complex, multifaceted process that requires understanding the interactions between the fiscal pressures facing local governments, the institutional pressures of working within a new regulatory framework and the political pressures of bringing together different levels of government with different perspectives and agendas. This dissertation has focused on tracing the factors affecting the individuals and institutions planning, preparing, responding and recovering from natural and man-made disasters. Using social network analysis, my study analyzes the interactions between the individuals and institutions that respond to these “focusing events.” In practice, it is the combination of budgetary, institutional, and political pressures or constraints interacting with each other which resembles a Complex Adaptive System (CAS). To investigate this system, my study evaluates the evolution of two separate sets of organizations composed of first responders (Fire Chiefs, Emergency Management Coordinators) and community volunteers organized in the state of Florida over the last fifteen years. Using a social network analysis approach, my dissertation analyzes the interactions between Citizen Corps Councils (CCCs) and Community Emergency Response Teams (CERTs) in the state of Florida from 1996- 2011. It is the pattern of interconnections that occur over time that are the focus of this study. The social network analysis revealed an increase in the amount and density of connections between these organizations over the last fifteen years. The analysis also exposed the underlying patterns in these connections; that as the networks became more complex they also became more decentralized though not in any uniform manner. The present study brings to light a story of how communities have adapted to the ever changing circumstances that are sine qua non of natural and man-made disasters

In recent years, a surprising new phenomenon has emerged in which globally-distributed online communities collaborate to create useful and sophisticated computer software. These open source software groups are comprised of generally unaffiliated individuals and organizations who work in a seemingly chaotic fashion and who participate on a voluntary basis without direct financial incentive. The purpose of this research is to investigate the relationship between the social network structure of these intriguing groups and their level of output and activity, where social network structure is defined as 1) closure or connectedness within the group, 2) bridging ties which extend outside of the group, and 3) leader centrality within the group. Based on well-tested theories of social capital and centrality in teams, propositions were formulated which suggest that social network structures associated with successful open source software project communities will exhibit high levels of bridging and moderate levels of closure and leader centrality. The research setting was the SourceForge hosting organization and a study population of 143 project communities was identified. Independent variables included measures of closure and leader centrality defined over conversational ties, along with measures of bridging defined over membership ties. Dependent variables included source code commits and software releases for community output, and software downloads and project site page views for community activity. A cross-sectional study design was used and archival data were extracted and aggregated for the two-year period following the first release of project software. The resulting compiled variables were analyzed using multiple linear and quadratic regressions, controlling for group size and conversational volume. Contrary to theory-based expectations, the surprising results showed that successful project groups exhibited low levels of closure and that the levels of bridging and leader centrality were not important factors of success. These findings suggest that the creation and use of open source software may represent a fundamentally new socio-technical development process which disrupts the team paradigm and which triggers the need for building new theories of collaborative development. These new theories could point towards the broader application of open source methods for the creation of knowledge-based products other than software.

The focus of this research is on identifying the determinants of local-level climate change adaptive capacity in Caribbean small island communities. A single case study approach was employed to assess retrospectively both internal and external factors that contributed to the adaptive capacity of Paget Farm, Saint Vincent and the Grenadines. The Caribbean region’s first solar-powered desalination plant was implemented in the community specifically as a climate change adaptation strategy and thus provides an ideal case for retrospective analysis. A series of semi-structured interviews with local residents and key stakeholders revealed a number of interacting social and institutional factors that contribute to community-based adaptive capacity. Further analysis of institutional factors was undertaken using Social Network Analysis, which enabled visualization and quantification of vertical and horizontal institutional integration of the networks formed during different phases of project implementation. The research extends scholarly understanding of the determinants that influence local-level climate change adaptive capacity and provides practical evidence that can assist small island communities to respond to a changing climate.