This thesis evaluates why the implementation of a tree plantation project in Chiapas, Mexico, called Scolel Te failed in its attempt to participate in the CDMs scheme. The Scolel Te project brings together farmers and local organisations into a network of exchange of resources that aims at producing an outcome that is only possible through the co-ordination and co-operation of all participants: the emission of carbon certificates. This thesis studies the co-ordination problems that local actors face at the moment of establishing the carbon projects by identifying how formal and informal mechanisms such as contracts, economic incentives, trust, and reputation, create or solve co-ordination problems in the Scolel Te network. The thesis also describes how changes in the distribution of power among actors affect the functioning of the network and how individual's interests and strategic alliances have the potential of derailing the aims of the environmental project. For such purposes, this thesis analyses the exchange relationships among actors at the micro level and identifies how exchange relationships evolve over time. Then an overall picture of the exchange relationships is presented (macro level) with focus in understanding how and why power in the network is exerted. Findings suggest that relying on economic incentives as the main mechanism to generate commitment among communities has failed to create stable exchange relationships in the long term. Trust and reputation are stronger mechanisms to achieve commitment. Moreover, we find that the ability to generate commitment depends highly on the generation of interdependencies between tree plantation projects and the main economic activities of local actors. However, type of land tenure, main economic activity, and pre-existing power relationships embedded at local level are also the principal factors that determine the dynamism of the social exchange relationships and commitment in the long-run. This thesis considers that co-ordination failure occurs because a lack of knowledge about the real dependencies between local actors and their natural resources in the design of CDMs. At macro level, this thesis found that the lack of accountability of the unregulated local carbon market at local level has created unintended incentives for actors to adopt less environmentally responsible strategies and disincentive participation in the CDMs.

Following the financial crisis that began in 2007, various groups and individuals demanded an ecologically diverse banking sector to help spread risk in the banking industry and to more effectively cater to customer needs. To date, however, measures to change retail banking have been limited to modest structural and incentive adjustments to boost competition and modify the banking culture which prompts an investigation about the nature of the ethical banking sector and its ability to grow and thrive. The lack of progress in reforming banking in the UK raises questions of whether and how we could encourage and sustain ethical, social and non-profit alternatives to current high street banks. Because prior academic research in ethical has been limited, the research aims to fill gaps with regards to understanding the network established between ethical banks their business models and to identify the type of intervention needed to promote ethical banking as an alternative to established mainstream retail banking.The research presented in this thesis investigates how the ethical banking sector is embedded in the UK financial services industry and draws out political-economic dynamics that facilitate as well as hinder the development of the sector. To this end, the thesis develops a conceptual framework that draws on literatures on industrial districts and embeddedness. The thesis also models and analyses the ethical banking network using social network analysis, before developing an understanding of ethical banks’ business models and how the sector is organised within the banking industry. Data on the banks’ relationships with other organisations were gathered through questionnaires, and interviews were conducted with respondent firms to explore ethical banking as a sector from the perspective of ethical banks themselves. In addition, company, industry and legislative publications have been analysed to add context and validate findings.At the broadest level, the results draw a picture of ethical banking as a diverse but disorganised subsector which is dominated by two players and lacks prospects to develop into an alternative banking sector that could compete with the full banking services offered by high street competition. Only if the sector manages to reorganise itself internally with support from external players could it form a more coherent and centralised subsector with a clear and shared understanding as to what its ambitions are. Thus the research highlights the potential of ethical banking which is expanding rapidly, but, at the same time, the research also raises the difficulties in developing ethical banking as a sector which retains its distinctiveness from high street banks. In sum, the research findings are in line with current ambitions to develop and promote a more diverse and sustainable UK banking industry: ethical banks should receive more attention from policy makers as they are a set of diverse actors that has grown significantly since the beginning of the financial crisis and, could if strengthened, contribute to developing a stronger retail banking sector more responsive to customer needs. Government efforts to reorganise banking should include developing ethical banking as an alternative to Plc retail banks which would change competition by increasing consumer choice instead of creating yet more large scale banks.

Most studies of 'cohesion' between urban residents focus separately on either social network structure or ideations with very little attention given to the intersection between spatial, structural and ideational dimensions of networks. This is problematic on two levels: firstly because attitudes and practices are formed in the context of personal social networks; and secondly because social interactions between residents are physically embodied and therefore spatially constrained. This thesis explores empirically the relationship between spatial cohesion (the extent to which a network is geographically localised or dispersed), structural cohesion (the extent to which a network is tight-knit or fragmented) and ideational cohesion (the extent to which residents have similar attitudes and practices). The social networks, attitudes and practices of white-British residents living in deprived urban localities of North Manchester are studied (survey, n=409; interview, n=53). Variances in forms of cohesion were found to have consequences for residents and localities. At the individual level, the spatial and structural shape of a resident's network was linked to their attitudes and behaviours. Attitudes and practices were 'framed' in the context of personal network structure exhibited through a set of resident 'roles'. This matters for urban cohesion because a person's social network structure influenced whether they liked their neighbourhood, trusted other residents, felt a sense of community or had found jobs through contacts. Previous studies have argued that contemporary urban networks have become fluid, dynamic and spatially dispersed. Yet this research found that although some people had networks that were geographically spread, most resident networks were made of localised, tight-knit, stable, long-term relations. Moreover, people with these cohesive, localised networks framed their experiences of urban cohesion differently to those with geographically spread and/or disconnected social networks. Particularly because the attitudes and practices of residents with localised, cohesive networks were very often habitual and socially reproduced. Social networks focus people's activities in such a way that not only constrains or enables current attitudes and practices but can also affect an individual's ability to change their future behaviour. At the locality level, the type of 'deprived' locality seemed to influence network structure. The structural, spatial and ideational distribution of cohesion at locality level provided neighbourhoods with different portfolios of social capital. Qualitative differences were observed between homogeneous-deprived (very low income, white areas) and socially mixed-deprived (white deprived areas with some class/ethnic mix) localities. People living in deprived-homogenous localities concentrated their networks within the local area and had few ties to residents of bordering areas, a sign of social distance. Conversely, residents of socially mixed-deprived localities had more potential to bridge ties to other neighbourhoods because their networks were not overly focused within the local area. Given that attitudes and practices are framed in the context of social network structure, it was argued that residents of deprived-homogeneous and socially mixed-deprived areas may experience and interpret urban cohesion differently and this has implications for universal policies of cohesion in deprived neighbourhoods. The thesis illustrates the interplay between spatial, structural and ideational forms of cohesion and highlights consequences for individual action and the generation of neighbourhood social capital. The originality of analysis and data synthesis are used to advance a relational and contextualised theory of urban cohesion and contribute to wider academic and policy debates on urban social networks and neighbourhood deprivation.

Please read the abstract (Summary) in the section 00front of this document / Dissertation (MEng (Electronic Engineering))--University of Pretoria, 2007. / Electrical, Electronic and Computer Engineering / MEng / Unrestricted

In this study social network analysis is used to empirically map out existing collaborative social networks influencing water governance in the Mkindo catchment, in Tanzania. I assess how existing social networks may affect the capacity to govern water and explore how knowledge about these networks can be used to facilitate more effective or adaptive water resources management. The study is the first of its kind to apply social network analysis to organizations influencing both blue water (the liquid water in rivers, lakes and aquifers) and green water (the soil moisture used by plants) at the catchment scale. Using a questionnaire and semi-structured interviews, social network data for 70 organizations was generated. With the help of social network analysis software1, the reciprocated collaborative interactions within the water governance network were traced, to better understand how the network facilitates and constrains individual actors, as well as the whole network, in managing water resources. Results show that there is currently no organization that coordinates the various land and water related activities at the catchment scale. Furthermore, there are important actors influencing water governance at the catchment scale, but they are not adequately integrated to the formal water governance system. Water user associations (WUA’s) are in the process of establishment, and could bring together actors presently not part of the formal governance system. However, at the moment the establishment of WUA’s seems to follow a top-down approach that fails to consider the existing informal organization of water users that are revealed through this social network approach. Instead of imposing institutional arrangements I argue that it is more promising and effective to identify and build on existing social structures. Social network analysis can help to identify existing social structures and points for interventions to increase the problem solving capacity of the governance network.

Ce projet utilise l’analyse de réseaux et la modélisation à base d’agents pour examiner des sujets classiquement traités mais qui peuvent maintenant être abordés, grâce aux riches données rencontrées dans le sud-ouest du Colorado et en France méridionale : comment les Gaules et les marchands méditerranéens établissaient leurs partenariats économiques, comment la violence a pu façonner le développement de niveaux divers de leadership, et comment les premiers agriculteurs interagissaient avec leur environnement. Pour écrire cette thèse composée de trois études de cas différents, deux dans le Sud-Ouest des États-Unis et un en France méridionale, nous utilisons des outils élaborés par les sciences de la complexité pour mieux aborder comment les individus de la préhistoire surmontaient les défis liés à l’acquisition de ressources. La modélisation à base d’agents et l’analyse de réseaux (sociaux et trophiques) nous permettront de décrire les processus décisionnels et d’analyser comment le partage de stratégies au sein du groupe peut entraîner une plus grande aptitude des individus à agir au sein du groupe. / This project utilizes network analysis and agent-based modeling to examine long-standing questions that can only now be asked with the rich data provided in southwestern Coloradoand southern France: how Gauls and colonists established economic partnerships, how violence may have shaped the development of multiple levels of leadership, and how earlyf armers interacted with their environments. Writing a dissertation composed of three distinct case studies, two from the U.S. Southwest and one from the south of France, I use tools developed in complexity science to better address how people in the past dealt with challenges related to resource acquisition. Agent-based modeling and network analysis (both social network analysis and trophic network analysis) will allow me to characterize human decision making processes and discuss how sharing of strategies within a group can lead to greater fitness of those in the in-group.

How are arms export choices made within a state? In this dissertation I use a foreign policy analysis framework to examine this question. I focus on examining each of the three primary levels of analysis in international relations as it relates to the main question. I begin with a typical international relations level and examine the characteristics of the two states that dominate the world arms trade: The United States and Russia. I then examine the full network of relations among all states in the international system that are involved in the sale or purchase of arms. To do this I use an Exponential Random Graph Model (ERGM) to examine these relations, which I derived from data on arms sales from the Stockholm International Peace Research Institute (SIPRI). I examine the arms sales in each decade from 1950 through 2010. In order to answer the question of how arms decisions are made within the state, I focus my inquiry on the United States and Russia. It is these states that have the practical capability to use arms transfers as a foreign policy tool. I examine the foreign policy making mechanisms in each of these states to determine how arms transfers can be used as a foreign policy tool. I examine and the bureaucratic institutions within each state and come up with a state ordering preference for how arms decisions are evaluated in each state. Finally, I use case studies to examine arms relations between the both the U.S. and Russia and three other states in each case. The other states were selected based on the pattern of sales between the two countries. I examine these sales to determine the impact of bureaucratic maneuvering and interest politics on the decision-making process within Russia and the United States. I find in my network analysis that the traditional measures of state power - military spending, regime type, and military alliances - do not account for the overall structure of the arms sale network. The most important factors in the formation of the arms sale network in each of the six decades that I study are specific configurations of triadic relations that suggest a continued hierarchy in the arms sale network. I find in my case study chapters that a simple model of state interest as a decision-making rule accounts for the decisions made by the different bureaucratic actors in the U.S. Russian arms sales are driven by a state imperative to increase Russia's market share, and there is high-level involvement in making different arms deals with other countries.

State supreme courts are autonomous institutions with significant power. Yet, despite this authority, state supreme courts routinely rely on one another to explain why and how they reached their decisions. This puzzle of why state supreme courts cite each other in their opinions led me to pose two questions. First, under what conditions do state supreme courts cite other states supreme courts? And second, to whom do they turn for guidance? To answer these questions, I propose a new theory for evaluating state supreme court citations, the social learning model. I borrow policy diffusion’s learning mechanism and I pair it with network theory and methods to explain peer-to-peer state supreme court citations practices. I argue that courts are social actors who interact, influence, and learn from one another, and the citations are communications by and between the courts. To model citations between courts, I apply a temporal exponential random graph network analysis model or TERGM. TERGMs simulate the evolution of the state-to-state citation network by including aspects of both the courts and the network structure. I argue that only by understanding how networks and issue areas evolve can we begin to understand how courts and justices make decisions. The network approach to citations specifically tests these endogenous relationships, it also directly models the complex dependencies of citation networks. My findings demonstrate the courts became more connected over time and no single state supreme court leader emerges. I find that citations are endogenous; what one court does affects other courts. I also discover that the area of law matters a lot and it is insufficient to pool all legal issues into a single model. Finally, state supreme courts do not cite state supreme courts who look like them. Overall, the evidence suggests the courts are learning from each other. The courts’ written language discloses the mechanism. Courts state their own case law does not provide a solution to the question presented and they must seek answers elsewhere. Additionally, the courts do not always cite the same state, as we would expect from emulation. Together, these findings demonstrate that state supreme courts are connected, they learn from one another.

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

Social media have become increasingly useful in identifying conversations during a crisis, particularly on Twitter where discussion tends to be public, accessible, and extensive. Through social media, individuals engage in social interaction and dialogue, making social media platforms a place where crisis coping activities may be identified, tracked and evaluated. This study examines crisis response of two separate crisis events, the terror attacks in Paris (2015) and in Barcelona (2017). Using semantic network analysis, this study examined dialogue surrounding each crisis over three days following the original crisis events, marked by the hashtags #Paris (24,728 tweets) and #Barcelona (27,338 tweets). Results show that the most dominant dialogue in the Paris and Barcelona terror attacks demonstrated central themes of information distribution, emotional expression, sense of community, and calls to action. More specifically, results show that the emotional connections trend positive in expressing community and unity. While most of the literature on crisis emphasizes negative response, this study shows that positivity during a crisis is a significant theme of discussions. Furthermore, this study showed resilience in efforts to seek positivity, build community, and create new normals, suggesting that social media engagement might help facilitate resilience.