Les réseaux sont présents dans pratiquement tous les aspects de la vie. Le monde quinous entoure comporte énormément de réseaux. Par exemple, les réseaux de communicationconstitués de téléphones, les réseaux électriques, les réseaux d’ordinateurs, le réseaudes lignes aériennes, ... etc, sont autant de réseaux importants dans la vie de chaque jour.Le cadre mathématique des réseaux est bien approprié pour décrire plusieurs systèmescomposés d’un grand nombre d’entités qui interagissent entre elles. Chaque entité est représentéepar un noeud du réseau et chaque interaction par un lien entre deux noeuds. Ilest donc possible de modéliser ces réseaux par des graphes. Pour la plupart de ces réseaux,la difficulté provient principalement du grand nombre d’entités, ainsi que de la façon dontelles sont interconnectées. Une approche naturelle pour simplifier de tels systèmes consistedonc à réduire leur taille. Cette simplification n’est pas faite aléatoirement, mais de tellefaçon à ce que les noeuds de la même composante aient plus de liens entre eux qu’avec lesautres composantes. Ces groupes de noeuds ou composantes sont appelés communautésd’intérêt. Notre thèse se positionne dans le domaine de l’étude des graphes sociaux. Elle s’intéresseprincipalement à l’étude de la robustesse des structures sociales émergentes dansles réseaux d’interactions. L’aspect de la robustesse des réseaux constitue un challengetrès important pour comprendre leur fonctionnement, le comportement des entités lesconstituant et surtout pour comprendre les interactions qui peuvent se produire entreelles, permettant l’émergence de certains comportements qui n’étaient pas du tout prévisiblesau préalable. Actuellement, les études de la robustesse des réseaux qui existentdans la littérature traitent cet aspect du point de vue purement structurel, i.e. toutes lesperturbations sont appliquées soit sur les noeuds, soit sur les arêtes du graphe. Pour cequi est de notre étude, nous nous sommes intéressés à définir une nouvelle stratégie qui sebase sur des perturbations appliquées sur les paramètres qui permettent l’émergence desgraphes sociaux dans les réseaux d’interaction. Cette façon d’aborder l’aspect robustessedes graphes constitue une nouvelle manière d’évaluer et de quantifier les changements quipeuvent intervenir dans les structures de ces graphes. / Networks are present in virtually all aspects of life. The world surrounding usincludes to many networks. For example, communication networks constituted of phones,electrical networks, computers networks, aerial lines network, ? etc, are such importantnetworks in our daily life. The mathematical framework of networks is well appropriatedto describe different systems composed of many entities interacting with each other. Eachentity is represented by a network node and each interaction by a link between twonodes. Therefore, it is possible to model these networks by graphs. For most of thesenetworks, the difficulty comes mainly from the large number of entities and the way theyare interconnected. A natural approach to simplify such systems is therefore to reducetheir size. This simplification is not made randomly, but in such a way that the nodes ofthe same component would have more connections between themselves than with othercomponents. These groups of nodes or components are called communities of interest.Our thesis is positioned in the field of social graphs study. It is mainly interested instudying the robustness of social structures emerging in interaction networks. The aspectof networks robustness is a very important challenge to understand their functioning,the behavior of the constituting entities and especially to understand the interactionsthat may occur between them, allowing the emergence of certain behaviors that were notpredictable at all in advance. Currently, studies of networks robustness that exist in theliterature treat this aspect from a purely structural point of view, ie, all perturbations areapplied either on nodes or on the edges of the graph. In terms of our study, we focused ondefining a new strategy based on perturbations applied on the parameters that allow theemergence of social graphs in interaction networks. This way to approach the robustnessappearance of the graphs is a new way to assess and quantify the changes that may occurin the structures of these graphs.

Studies of human relationships in anthropology, religion, community studies and psychology have determined that willingness to sacrifice plays an important role in reinforcing and strengthening social bonds. It is remarkable that given the increasing prominence of the relationship marketing paradigm, marketers have spent little time investigating willingness to sacrifice as a potential variable of interest. This dissertation extends relationship marketing theory by defining, developing and testing the willingness to sacrifice construct in the context of brand communities. It not only establishes a role for willingness to sacrifice in the nomological network of relationship marketing, but also develops a typology of sacrifices members make in brand communities. Results from two experiments and a field study of two brand communities suggest there are significant relationships between willingness to sacrifice and established constructs in relationship marketing research, such as identification, satisfaction with peers, and norms of reciprocity. Moreover, these findings indicate that willingness to sacrifice is positively associated with beneficial marketing outcomes such as word of mouth, purchase intentions and brand community longevity. By integrating literature from personal psychology, sociology anthropology–all of which discuss sacrifice in terms of how it can benefit and strengthen relationships– this research challenges the conventional marketing assumption that sacrifice is merely “the price one pays.” Taken together, these studies enrich our understanding of willingness to sacrifice in a marketing context, and more specifically, identify a process through which it contributes to brand community success and related marketing outcomes. / Thesis (Ph.D, Management) -- Queen's University, 2014-04-09 10:41:22.156

L'étude de structures de communautés dans les réseaux devient de plus en plus une question importante. La connaissance des modules de base (communautés) des réseaux nous aide à bien comprendre leurs fonctionnements et comportements, et à appréhender les performances de ces systèmes. Une communauté dans un graphe (réseau) est définie comme un ensemble de nœuds qui sont fortement liés entre eux, mais faiblement liés avec le reste du graphe. Les membres de la même communauté partagent les mêmes centres d'intérêt. La plupart des travaux qui existent dans ce domaine se scindent en deux grandes thématiques: la détection de communautés et l'analyse de communautés. La détection de communautés consiste à trouver les communautés dans un réseau donné, sans connaître à priori ni la taille ni le nombre des communautés. La partie analyse de communautés, quant à elle, consiste à étudier les propriétés structurelles et sémantiques des communautés détectées et de celles du réseau étudié. Dans cette thèse, nous nous intéressons à l'étude de structures de communautés dans les réseaux. Nous contribuons dans les deux parties, analyse et détection de communautés. Dans la partie analyse de communautés, nos contributions sont l'étude des communautés dans les réseaux de communication et l'étude des communautés dans les services Web. D'une part, nous étudions l'émergence de communautés dans les réseaux de communication. Nous proposons une classification de structures de communautés émergées dans un réseau de communication donné. Nous modélisons les réseaux par les graphes et nous les caractérisons par un ensemble de paramètres. Nous concluons par une corrélation directe entre le réseau initial et les types de structures de communautés émergées. D'autre part, nous étudions les communautés dans les logs de services Web. Nous analysons les historiques d'exécution (les fichiers logs) afin de découvrir les protocoles métiers de services (séquences de messages échangés entre le service et le client pour aboutir à un but donné). Nous modélisons les logs par les graphes, et nous cherchons l'ensemble de conversations (communautés) issues de notre graphe de messages (le graphe de messages est un graphe induit du graphe de logs). Notre contribution dans la partie détection de communautés, est la proposition d'un algorithme de détection de communautés basé sur les motifs utilisant l'optimisation spectrale. Nous définissons une matrice de modularité motif (particulièrement, le triangle), et nous utilisons l'algorithme de décomposition et d'optimisation spectrale pour détecter les communautés basées sur des motifs. Nous montrons l'apport des communautés basées sur les motifs en appliquant notre algorithme sur des réseaux sociaux connus dans la littérature et en comparant les communautés basées sur les motifs trouvées avec les communautés classiques. / The study of the sub-structure of complex networks is of major importance to relate topology and functionality. Understanding the modular units (communities) of graphs is of utmost importance to grasping knowledge about the functionality and performance of such systems. A community is defined as a group of nodes such that connections between the nodes are denser than connections with the rest of the network. Generally, the members of one community share the same interest. Many efforts have been devoted to the analysis of the modular structure of networks. The most of these works are grouped into two parts: community detection and community analysis. Community detection consists on finding communities in networks whithout knowing there size and number. While the community analysis deals the study of the structural and semantic properties of the emerged communities, and the understanding of the functionality and the performance of the network. In this thesis, we are interested on the study of the community structures in networks. We give contributions in both community analysis and community detection parts. In the community analysis part, we study the communities of communication networks and the communities in web services. On the one hand, we study the community emergence in communication networks. We propose a classification of the emerged community structures in a given network. We model the networks by graphs and we characterize them by some parameters (network size, network density, number of resources in the network, number of providers in the network, etc.). We give also a direct correlation between the network parameters and the emerged community structures. On the other hand, we study the communities in the web service logs. We aim to discover the business protocol of services (sequences of messages exchanged between the service and a client to achieve a given goal). We analyze the log files and we model them by graphs. In our final tree graph (message graph), the paths represent the conversations (communities). In the community detection part, the main goal of our contribution is to determine communities using as building blocks triangular motifs. We propose an approach for triangle community detection based on modularity optimization using the spectral algorithm decomposition and optimization. The resulting algorithm is able to identify efficiently the best partition in communities of triangles of any given network, optimizing their correspondent modularity function.

Creativity is increasingly becoming both an important issue in our rapidly changing society, and a popular subject of research. Research findings are beginning to conceptualize creativity as a much more complex process and studies are now focusing on the effects of social interaction and collaborative efforts on creativity as well as the potential impact of technology on collaboration and the creative process itself. This study looks at the influence of both collaboration and technology on the creative process to develop a clearer picture of the way in which they intersect. Due to the complexity of this study, two theoretical frameworks (Communities of Practice and Genex Framework) have been employed to inform the development of the study and to assist in contextualizing the results. To this end, this mixed-methods study collected data both from fashion design students enrolled in the third year of a Bachelor of Fashion Design program, and from their faculty. Data gathering methods included personal semi-structured interviews with both students (n = 13) and faculty (n = 9) and an online questionnaire with a larger group of students (n = 65). The research questions that framed this study focus on developing an initial understanding of the creative process as experienced by these students and then exploring in depth the ways that collaboration and working in community affect the creative process, as well as the impact of technology in supporting both creativity and collaboration. Results suggest that technology was indeed a valuable support in the creative process through its ability to facilitate particular kinds of collaborative practices, including brainstorming, developing and sharing ideas, and giving and receiving feedback. Such practices directly affected the creative process by enhancing the development of more professional sketches as well as facilitating the collaborative efforts of the members of the design community. Finally, the implications of these results for curriculum design and the appropriate choice of pedagogical approaches are discussed. The results presented will help to support curriculum designers and instructors who seek to encourage creative endeavour to focus on effective technological tools as well as strategies that promote collaboration and a sense of community in order to achieve these ends.

Creativity is increasingly becoming both an important issue in our rapidly changing society, and a popular subject of research. Research findings are beginning to conceptualize creativity as a much more complex process and studies are now focusing on the effects of social interaction and collaborative efforts on creativity as well as the potential impact of technology on collaboration and the creative process itself. This study looks at the influence of both collaboration and technology on the creative process to develop a clearer picture of the way in which they intersect. Due to the complexity of this study, two theoretical frameworks (Communities of Practice and Genex Framework) have been employed to inform the development of the study and to assist in contextualizing the results. To this end, this mixed-methods study collected data both from fashion design students enrolled in the third year of a Bachelor of Fashion Design program, and from their faculty. Data gathering methods included personal semi-structured interviews with both students (n = 13) and faculty (n = 9) and an online questionnaire with a larger group of students (n = 65). The research questions that framed this study focus on developing an initial understanding of the creative process as experienced by these students and then exploring in depth the ways that collaboration and working in community affect the creative process, as well as the impact of technology in supporting both creativity and collaboration. Results suggest that technology was indeed a valuable support in the creative process through its ability to facilitate particular kinds of collaborative practices, including brainstorming, developing and sharing ideas, and giving and receiving feedback. Such practices directly affected the creative process by enhancing the development of more professional sketches as well as facilitating the collaborative efforts of the members of the design community. Finally, the implications of these results for curriculum design and the appropriate choice of pedagogical approaches are discussed. The results presented will help to support curriculum designers and instructors who seek to encourage creative endeavour to focus on effective technological tools as well as strategies that promote collaboration and a sense of community in order to achieve these ends.

在傳統的企業思維中，價值乃是由企業創造的，由企業單獨決定其產品和服務提供什麼價值，消費者僅僅代表對公司產品的需求；但隨著產業環境的發展，尤其是網路經濟時代的來臨，生產者與消費者之間的界限開始模糊。在過去資訊單向流通的網路世界中，人們在網路上代表的僅僅是一個創造流量的虛擬人物，然而隨著資訊科技的進步，網路技術的發展，人們在網際網路中開始彼此協作，發揮集體智慧向全世界發聲，即「價值共創」的概念。從Linux開放原始碼成功以來，許多企業已經逐漸了解到使用者參與創新、使用者虛擬社群參與企業產品開發的重要性，企業不再能獨自生產和管理知識，而是需要與它們的使用者共同創造知識；同時，人們也了解到透過結合價值共創的概念，虛擬社群平台可以發揮多大的效用，並且在其他領域也有許多類似概念的應用。 科技的協助讓使用者可依據其個別的興趣、需求等動機組成或進入不同的興趣型虛擬社群平台，此類平台除了結合對某一特定議題或事物有共同喜好的人們、高度人際之間的互動與溝通、經由網站所提供之平台分享交流彼此的心得與看法之外，尚有組織設計正式化程度低與集權化低之特色，以及此類社群對於參與者無特殊專業知識與技能之進入門檻之特色。因上述之特色，興趣型虛擬社群平台需要集眾多使用者之分享，才能在無特殊專業門檻的情況下，以內容累積出具有價值之資料庫。 本研究針對興趣型虛擬社群平台進行探討，透過文獻中得知之社群經營成功關鍵要素：「價值共創的環境」、「誘因機制」、「知識管理」檢視個案興趣型虛擬社群平台，並發現三者之間有順序性之關係。首先透過良好設計的「價值共創」社群平台環境，吸引使用者參與，其結果可以加強社群平台自身之競爭優勢。第二階段興趣型社群平台應該透過明顯且簡易得到之金錢誘因吸引使用者，使其有動機參與進入興趣型社群平台，而在使用者數量提升之後，透過管理機制之設計，產生心理誘因，加強使用者之重複拜訪與投入的行為，即透過正確而有效的「誘因機制」提升興趣型社群平台運作之人流量與忠誠度。於累積足夠的使用者及高度黏著度之後，興趣型社群平台應該透過「知識管理」建立機制，將社群平台上累積之知識形成資料庫，以吸引更多的使用者加入，串聯具互補性質的合作夥伴，同時促進更高的社群平台黏著度，並且進而利用資料庫，創造可能的多樣化獲利來源。 / The research aims to focus on the communities of interest, which is now the mainstream of communities on the Internet. With respect to the lack of related research on the operation of communities of interest, this research will examine three factors that are key to the operation of this kind of communities and research how these three factors work and how business managers plan a strategy for the operation of communities of interest. The research will take iPeen and Fandora, both of which are rising stars communities in Taiwan, as case study communities. The study reveals that there are some factors that are key to the success of communities. By examining the factors, we can see how they work and how they would lead to the victory in the heated online communities war. According to the research, a value co-creation environment, the incentives and knowledge management would be the key to the success of operation of communities of interest. The management team of communities of interest can use these three key factors step by step through strategic planning. In the final conclusion and suggestion, the research aims at the future participants in the industry and provides solutions to the strategic planning regarding previously found key factors and referred cases.

Modeling the "thick description" of photographs began at the intersection of personal and institutional descriptions. Comparing institutional descriptions of particular photos that were also used in personal online conversations was the initial phase. Analyzing conversations that started with a photographic image from the collection of the Library of Congress (LC) or the collection of the Manchester Historic Association (MHA) provided insights into how cultural heritage institutions could enrich the description of photographs by using informal descriptions such as those applied by Facebook users. Taking photos of family members, friends, places, and interesting objects is something people do often in their daily lives. Some photographic images are stored, and some are shared with others in gatherings, occasions, and holidays. Face-to-face conversations about remembering some of the details of photographs and the event they record are themselves rarely recorded. Digital cameras make it easy to share personal photos in Web conversations and to duplicate old photos and share them on the Internet. The World Wide Web even makes it simple to insert images from cultural heritage institutions in order to enhance conversations. Images have been used as tokens within conversations along with the sharing of information and background knowledge about them. The recorded knowledge from conversations using photographic images on Social Media (SM) has resulted in a repository of rich descriptions of photographs that often include information of a type that does not result from standard archival practices. Closed group conversations on Facebook among members of a community of interest/practice often involve the use of photographs to start conversations, convey details, and initiate story-telling about objets, events, and people. Modeling of the conversational use of photographic images on SM developed from the exploratory analyses of the historical photographic images of the Manchester, NH group on Facebook. The model was influenced by the typical model of Representation by Agency from O'Connor in O'Connor, Kearns, and Anderson Doing Things with Information: Beyond Indexing and Abstracting, by considerations of how people make and use photographs, and by the notion of functionality from Patrick Wilson's Public Knowledge, Private Ignorance: Toward a Library and Information Policy. The model offers paths for thickening the descriptions of photographs in archives and for enriching the use of photographs on social media.