Increased international competitiveness to host sport mega-events indicates their perceived value in stimulating regional and national economic, social and cultural development. In the context of broader governmental public opinion management strategies, sport mega-events hold the potential to mobilize soft power resources of the host country, expressed in values, culture and policies, and engage with and influence the publics of other countries. This thesis investigates the significance of sport mega-events for the host country’s public diplomacy strategies and practice by exploring the concepts of public diplomacy, sport mega-events, soft power and national image within a multi-disciplinary conceptual framework. The analysis of scholarly literature, official and media reports reveals how aspects of reputation, credibility, and legitimacy guide both foreign public opinion and the practice of public diplomacy in conjunction with sport mega-events. Moreover, international reputation of the host nation, including status, prestige and image, appeared to benefit the most as a result of strategic application of sport mega-events to public diplomacy. This can be achieved by proving functional reputation though demonstration of financial and organizational success. Alternatively, social reputation of the host is at risk of sustaining considerable damage as a result of resistance from social activists groups, thus requiring extensive damage control efforts of the host country's image. The conclusions drawn from this study raise significant questions about the potential of sport mega-events being effectively used for public diplomacy and the experience of the host governments, revealing functional competence as having the greatest potential to influence public diplomacy strategy built around hosting sport mega-events.

The aim of this study is to understand the influence of online discussion forums during times of crisis. These forums can be considered as a form of social media, a relatively new form of technology that is constantly evolving and gaining in popularity. It has become an important medium, and can be integral in communications plans, specifically with regards to crisis communication. Through the use of these media, message delivery has unbelievable breadth and speed, making it crucial to understand its implications in crisis events. In order to understand social media’s implications in reputation management, during times of crisis, an ethnographic content analysis was conducted through the analysis and comparison of comments posted on news forums and media documents issued by the NHL during the 2012-2013 lockout. Literature suggests the importance of relationship management prior to crisis onset, as social media has the potential to inflame and contaminate the perceptions of others. Through social media, the formation and emergence of an engaged and active public was observed and studied. However, when considering traditional crisis communication theories, results from this particular case are counterintuitive; the findings counter traditional crisis communication theories, suggesting that cases such as this one are to be investigated further.

This research focuses on the redesign of trust and reputation algorithms in the context of hierarchically structured Peer-to-Peer (P2P) networks with Chord, a scalable P2P lookup service for Internet applications. Chord, which is an open source project, is an overlay network based on a distributed hash table(DHT), and all peers in Chord are arranged around a circle. In this work, we propose four adapted trust and reputation algorithms for hierarchically structured P2P networks: EigenTrust, PowerTrust, Absolute Trust and NodeRanking. EigenTrust is one of the most well-known trust and reputation algorithms, as well as the most simple. To calculate the reputation, EigenTrust needs to normalize trust and rely on pre-trusted peers. Like EigenTrust, PowerTrust relies on feedback and the use of a distributed ranking mechanism. It chooses a limited number of power nodes with a high reputation. By combining a random walk strategy and the power nodes, it improves accuracy of global reputation. AbsoluteTrust does not require normalization of trust, pretrusted peers or any centralized authority. Weighted average combined with feedback from peers is employed to determine trust. NodeRanking relies on both individual reputation and social relationship to compute the trust value. NodeRanking evaluates reputation using local information. A node's reputation value can be readily determined by the number of references from other nodes in the network. These adapted algorithms are capable of handling a huge number of nodes disseminated in different rings, which improves complexity and reduces the number of malicious nodes in a hierarchical context. Furthermore, we describe the components of the hierarchical model architecture and present and discuss the results from the experiments. These experiments are employed to verify and compare reduction of downloads from malicious peers, load distribution and residual curl in at structured networks and in hierarchically structured networks.

A partir d’une enquête mêlant entretiens, observations et analyses d’archives, cette thèse rend compte du marché des Grands Crus bordelais en montrant comment les phénomènes de réputation interviennent dans les activités et les relations de concurrence entre professionnels. La première partie de la thèse montre que les classements viticoles, en tant que cadres des réputations des Crus et des individus, instituent une clôture statutaire du marché. Les cas du classement de 1855 en Médoc et du classement de Saint-Emilion illustrent la stabilité de la configuration statutaire et la difficulté de réviser les hiérarchies locales. La deuxième partie est consacrée aux chiffres de la réputation (prix et notes) qui, loin d’être purement aléatoires et indépendants, sont enchâssés dans la configuration statutaire formée par les classements et dans l’organisation sociale de la « place de Bordeaux ». L’étude successive de l’architecture des prix, de la formation des prix de sortie en primeurs, et de l’incidence des notes des critiques influents, permettra d’évaluer les enjeux et les conséquences de la commensuration sur la construction de la valeur des vins. La troisième partie de la thèse a pour ambition d’examiner la place des noms et des catégories dans les carrières de certains professionnels bordelais. Le marché des consultants œnologiques est étudié à travers la question de la « signature » des vins, tandis que la catégorie des « vins de garage » permet d’observer comment s’articulent les différents types d’évaluations dans les trajectoires d’entrepreneurs. / This PhD is based upon a fieldwork including in-depth interviews, observations and historical source analysis. It focuses on the Bordeaux “Grands Crus” Market by showing how reputations play a key role in professionals’ activities and competition relationships. The first section underlines that wine rankings, as reputation frames for growths and individuals, foster a status closure of the market. The Medoc and Saint-Emilion classifications illustrate the stability of the status configuration and the difficulty for changing the local hierarchies. The second section focuses on reputation numbers (prices and rates), which are embedded in a status configuration grounded both on rankings and on the social organisation of the “place de Bordeaux”. The study of the prices’ architecture, the formation of “en primeurs” release prices and the role of critics’ rates leads us to appreciate the consequences of commensuration on the building of wine values. The third section aims at examining the role of names and categories in some professionals’ careers. We study the flying winemakers’ market through the issue of wine “signature”, while the category of “garage wines” allows to analyse how the different kinds of evaluations overlap in entrepreneurs” trajectories.

The topic of the thesis "Human resources marketing in Hewlett-Packard, s.r.o." is the analysis of practical use of human resources marketing in the company and a perception of company's brand between students/recent graduastes and a proposal for improvements in particular areas of human resources management. The theoretical part deals with particular personnel activities in the company. The practical part focuses on the analysis of the situation in human resources marketing in the Hewlett-Packard, s.r.o. In the conclusion are some recommendations and proposals to solve the discovered problems and imperfections.

Trust plays an important role in our daily life, both implicitly and explicitly. Our decisions are based on our estimation of how trustworthy a person is or how reliable a service is. Consequently, there has been a rise in trust systems that model human trust in a virtual or computing environment. These trust systems or trust models help to bridge the gap of human feelings and intuition in an unfamiliar environment. Trust models collect information regarding the participants' activities and give a trust rating based on observed activities. In a network environment, a plethora of network devices are in constant communication as data packets are transported from source to destination. The autonomous nature of network environments and devices make it difficult to monitor the services and devices from a central point. Security mechanisms, such as IPSec, exist in routing protocols to safeguard network packets travelling in a network, however routing devices that act as service providers are not protected by malicious attacks. For example, an attack aimed at the routing architecture of a network involves a routing device advertising itself as another routing device in order to divert network traffic away from its intended destination. This dissertation investigates trust models in network environments as a possible approach to predict and ultimately eliminate at- tacks on routing devices. To accomplish this, the role of routing devices as service providers and requesters must be stated explicitly. Activities on a routing device must be collected and used to determine the trust level of the routing device. This dissertation presents the TSONE - Trust in Service-Oriented Net- work Environment - model. The model incorporates traditional service- oriented architecture (SOA) principles to define a service-oriented network environment. Services in this environment are then defined. Furthermore the characteristics of this environment are adapted from SOA principles. An approach is defined to collect and measure activities on routing devices. This is later used to determine the trust level of the routing device. Finally, a pro- to type illustrates that incorporation of trust models is a possible option in assessing availability and reliability of routing devices. / Dissertation (MSc)--University of Pretoria, 2011. / Computer Science / unrestricted

In recent years, corporate reputation has gained the attention of many scholars in the strategic management and related fields. There is a general consensus that higher corporate reputation is positively related to firm success or performance. However, the link is not always straightforward; as a result, it calls for researchers to dedicate their efforts to investigate the causes and effects of firm reputation and how it is related to performance. In this doctoral dissertation, innovation is suggested as a mediating variable in this relationship. Innovation is a critical factor for firm success and survival. Highly reputed firms are in a more advantageous position to attract critical resources for innovation such as human and financial capital. These firms face constant pressure from external stakeholders, e.g. the general public, or customers, to achieve and remain at high levels of innovativeness. As a result, firms are in constant search, internally or externally, for new technologies expanding their knowledge base. Consequently, these firms engage in firms acquisitions. In the dissertation, the author assesses the effects of domestic versus international acquisitions as well as related versus unrelated acquisitions on the level of innovativeness and performance. Building upon an established measure of firm-level degree of internationalization (DOI), the dissertation proposes a more detailed and enhanced measure for the firm’s DOI. It is modeled as an interaction effect between corporate reputation and resources for innovation. More specifically, firms with higher levels of internationalization will have access to resources for innovation, i.e. human and financial capital, at a global scale. Additionally, the distance between firms and higher education institutions, i.e. universities, is considered as another interaction effect for the human capital attraction. The dissertation is built on two theoretical frameworks, the resource-based view of the firm and institutional theory. It studies 211 U.S. firms using a longitudinal panel data structure from 2006 to 2012. It utilizes a linear dynamic panel data estimation methodology for its hypotheses analyses. Results confirm the hypotheses proposed in the study.

Na Web 2.0 são encontrados sistemas com alto volume de interação social. Alguns desses sistemas oferecem cálculo de reputação ou alguma forma de classificação de usuários ou do conteúdo compartilhado. Contudo, em muitos casos, esse valor de reputação resultante é obtido somente a partir de dados quantitativos ou qualitativos. O objetivo deste trabalho é elaborar um modelo para o cálculo de reputação em comunidades on-line, baseando-se em dados qualitativos e quantitativos provenientes da interação dos próprios participantes da rede, a fim de potencializar a colaboração entre os membros e fornecer um meio de cálculo resistente a algumas das vulnerabilidades comuns em sistemas de reputação, como tolerância a ruídos e ataques Sybil. Para atingir esse objetivo é realizada uma adaptação do algoritmo PageRank, definida como CR (Collaborative Reputation) para obter uma ordenação dos usuários a partir de suas interações. Para avaliação, adotamos um conjunto de dados do sítio Epinions.com, com o qual foi realizada uma análise comparativa dos resultados obtidos a partir do modelo proposto com outros três algoritmos correlatos ao trabalho apresentado. Dentre as técnicas usadas na análise estão: diversidade de valores, comparação da ordenação, estudo comparativo de cenários, tolerância a ruídos e robustez contra ataques tipo Sybil. Os algoritmos usados na avaliação são: o PageRank original e o algoritmo ReCop, usados para a identificação de usuários relevantes, e o algoritmo LeaderRank usado para a identificação dos usuários com maior prestígio na rede. Os resultados indicam que o modelo proposto é mais sensível às interações dos usuários em comparação aos outros modelos usados na avaliação, mas é mais eficiente a ataques Sybil. / In the Web 2.0, there are systems with high volume of social interaction. Some of these systems offer reputation calculation or some form of classification of users or shared content,. However, in many cases, this reputation value is obtained solely from quantitative or qualitative data. The objective of this work is to develop a model for the reputation calculation in online communities, based on qualitative and quantitative data from the interaction of the participants of a social network, in order to potentiate the collaboration between users, and to provide a resistant environment for some of the vulnerabilities present in reputation systems. To achieve this goal we defined an adaptation of the PageRank algorithm, defined as CR (Collaborative Reputation), to obtain a rank of users based on their interactions in the network. For evaluation, we used a dataset from the site Epinions.com. With that database, we executed a comparative analysis of the results of the proposed algorithm and of three other algorithms related to the presented work. The procedures used in the analysis were: diversity of values, comparison of ordination, comparative study of scenarios, noise tolerance and robustness against Sybil attacks. The algorithms used in the comparison were: the original PageRank algorithm and ReCop, used to identify relevant users, and the algorithm LeaderRank, which is used for identification of the most prestigious users in the network. The results showed that the proposed model is more sensitive to the interactions of users, but its performance on Sybil attacks is better than the others.

L'enjeu de ma thèse est de mettre au jour les enjeux qui entourent la croissance des données trouvables en ligne sur les personnes, la multiplication et le fort usage des espaces numériques de sociabilité dont la vocation privée ou professionnelle peuvent tendre à mélanger les deux sphères. L'enjeu du droit des données est confronté au cas du recrutement. Cas où la volonté de valorisation de soi de la part de candidats en recherche d'emploi rencontre le besoin d’évaluation de la part des recruteurs. Le cas du recrutement permet d'aborder différents marchés émergents autour de la réputation numérique, d'interroger les pratiques de part et d'autre du marché du travail (exposition des candidats et recherches des recruteurs) et d'apporter des éléments de connaissances sur les normes de visibilité en cours d'établissement. / The aim of my thesis is to underline what is at stake with the phenomenon of the massive growth of online personal data that we have witnessed for the last decade. This issue is seen through the case of hiring on the labor market. Candidates may want to disclose positive information about themselves and recruiters need to gather as much information as they can to evaluate potential candidates. This example allow us to investigate a new market for online reputation and to bring to knowledge the new norms of visibility and privacy in the age of social media.

De nos jours, la popularité des réseaux sociaux (RS) est en constante progression. En effet, de plus en plus d’utilisateurs interagissent dans le monde virtuel, soit en y exprimant des opinions, en partageant des expériences, en réagissant aux avis d’autrui ou encore en échangeant des idées, en fonction de leurs qualités : influents, populaires, dignes de confiance, etc.. Dans la littérature, l’influence a fait l'objet d'une attention particulière ces dernières années. En effet, de nombreux domaines, dont l’Analyse des Réseaux Sociaux (ARS) et les systèmes de recommandation ont étudié l’influence, sa détection, la propagation de son effet et sa mesure. Ainsi, des modèles d'identification et d'estimation de l'influence sont aujourd'hui largement utilisés dans de nombreuses applications dédiées au marketing, aux campagnes politiques/sociales, etc. De plus, les interactions entre utilisateurs indiquent non seulement l’influence mais aussi la confiance, la popularité ou la réputation. Cependant, ces notions sont encore vaguement définies et il n'existe pas de consensus dans la communauté ARS. Définir, distinguer et mesurer la force de ces relations entre les utilisateurs posent également de nombreux défis, à la fois théoriques et pratiques, qui restent à explorer. La modélisation de l’influence pose de multiples défis et les méthodes actuelles de découverte et d’évaluation n’explorent pas encore pleinement les différents types d’interactions et ne sont en général pas applicables à plusieurs RS. En outre, la prise en compte de la dimension temporelle dans le modèle d’influence est importante, difficile et nécessite un examen plus approfondi. Enfin, l’exploration de liens possibles entre des notions, telles que l’influence et la réputation, reste un sujet ouvert. Dans cette thèse, nous nous focalisons sur les quatre concepts qualifiant les utilisateurs : influence, réputation, confiance et popularité, pour la modélisation de l'influence. Nous analysons les travaux existants utilisant ces notions et comparons leurs différentes interprétations. Par cette analyse, nous mettons en avant les caractéristiques essentielles que ces concepts devraient inclure, et nous en effectuons une analyse comparative. Cela nous permet d'établir une classification globale des différentes interprétations des notions selon leur niveau d'abstraction et leurs divergences ; cela constitue la première, contribution de cette thèse. En conséquence, nous proposons un modèle théorique de l'influence ainsi qu'une ontologie associée décrivant ce concept. Nous présentons également une variante de l'influence, inexplorée à ce jour dans le domaine de l’ARS, la micro-influence. Celle-ci cible un phénomène nouveau dans les RS que sont les utilisateurs avec une faible audience, mais fortement impliqués ; ces derniers apparaissent en effet comme ayant un impact fort malgré tout. En s'appuyant sur ces définitions, nous proposons ensuite un modèle pratique dénommé ARIM (Action-Reaction Influence Model). Ce modèle considère le type, la qualité, la quantité et la fréquence des actions réalisées par les utilisateurs, et ce en étant compatible avec différents RS. Nous abordons également la quantification de l'influence au cours du temps et la représentation de ses effets de causalité. Pour cela, nous considérons un type spécifique de RS: les réseaux de citations, particulièrement sensibles au temps. Ainsi, nous proposons un modèle, TiDIE (Time Dependent Influence Estimation), qui détermine l'influence, sur une période de temps, entre les communautés de ces réseaux. Enfin, nous combinons l’influence et la réputation avec le modèle TiDIE, afin d’étudier les dépendances entre elles. Nous proposons une méthode de transition, ReTiDIE, utilisant l’influence pour obtenir la réputation. Pour chacune de nos approches, des expérimentations ont été menées sur des jeux de données réels et ont montré la pertinence de nos méthodes / Online social networks are constantly growing in popularity. They enable users to interact with one another and shifting their relations to the virtual world. Users utilize social media platforms as a mean for a rich variety of activities. Indeed, users are able to express their opinions, share experiences, react to other users' views and exchange ideas. Such online human interactions take place within a dynamic hierarchy where we can observe and distinguish many qualities related to relations between users, concerning influential, trusted or popular individuals. In particular, influence within Social Networks (SN) has been a recent focus in the literature. Many domains, such as recommender systems or Social Network Analysis (SNA), measure and exploit users’ influence. Therefore, models discovering and estimating influence are important for current research and are useful in various disciplines, such as marketing, political and social campaigns, recommendations and others. Interestingly, interactions between users can not only indicate influence but also involve trust, popularity or reputation of users. However, all these notions are still vaguely defined and not meeting the consensus in the SNA community. Defining, distinguishing and measuring the strength of those relations between the users are also posing numerous challenges, on theoretical and practical ground, and are yet to be explored. Modelization of influence poses multiple challenges. In particular, current state-of-the-art methods of influence discovery and evaluation still do not fully explore users’ actions of various types, and are not adaptive enough for using different SN. Furthermore, adopting the time aspect into influence model is important, challenging and in need of further examination part of the research. Finally, exploring possible connections and links between coinciding notions, like influence and reputation, remains to be performed.In this thesis, we focus on the qualities of users connected to four important concepts: influence, reputation, trust, and popularity, in the scope of SNA for influence modeling. We analyze existing works utilizing these notions and we compare and contrast their interpretations. Consequently, we emphasize the most important features that these concepts should include and we make a comparative analysis of them. Accordingly, we present a global classification of the notions concerning their abstract level and distinction of the terms from one another, which is a first and required contribution of the thesis. Consequently, we then propose a theoretical model of influence and present influence-related ontology. We also present a distinction of notion not yet explored in SNA discipline -- micro-influence, which targets new phenomena of users with a small but highly involved audience, who are observed to be still highly impactful. Basing on the definitions of the concepts, we propose a practical model, called Action-Reaction Influence Model (ARIM). This model considers type, quality, quantity, and frequency of actions performed by users in SN, and is adaptive to different SN types. We also focus on the quantification of influence over time and representation of influence causal effect. In order to do that, we focus on a particular SN with a specific characteristic - citation network. Indeed, citation networks are particularly time sensitive. Accordingly, we propose Time Dependent Influence Estimation (TiDIE), a model for determining influence during a particular time period between communities within time-dependent citation networks. Finally, we also combine two of the abovementioned notions, influence and reputation, in order to investigate the dependencies between them. In particular, we propose a transition method, ReTiDIE, that uses influence for predicting the reputation. For each of the proposed approaches, experiments have been conducted on real-world datasets and demonstrate the suitability of the methods