Aquest treball de recerca se centra en un dels processos més rellevants de les persones: l’intercanvi de coneixements (IC). El coneixement pot ser explícit o tàcit. L’explícit es pot codificar, estructurar i emmagatzemar de manera que pugui estar disponible. El coneixement tàcit, conegut també com a tacit knowing, és l’acció de conèixer que no es pot codificar ni estructurar, sinó que depèn de les experiències, el criteri i els valors de la persona. Les xarxes socials informals de les organitzacions esdevenen un mitjà pel qual es pot facilitar la transmissió del tacit knowing, de manera que mitjançant l’anàlisi de xarxes socials (social network analysis, SNA) es poden entendre i analitzar les relacions entre les persones, més enllà de les estructures formals i jeràrquiques. Aquesta situació és rellevant perquè l’alta direcció potenciï, i no cerqui d’estructurar o de controlar, aquestes xarxes socials i amb una gestió adequada incentivi que el coneixement flueixi a través d’elles. Es plantegen els objectius següents: 1) establir l’impacte de la complexitat de tasques en la intensitat de la interacció de xarxes socials en una organització; 2) establir l’impacte de la complexitat de tasques en el procés d’intercanvi de coneixement, i 3) verificar si hi ha alguna relació entre la intensitat de la interacció de les xarxes socials en el procés d’intercanvi de coneixement (IC). En la recerca, s’ha administrat una enquesta a tres organitzacions peruanes intensives en coneixement. Es planteja que, com més complexes siguin les tasques, la propensió de la persona a intercanviar coneixements ha de ser més gran. Els criteris de classificació de la complexitat es basen en la multiplicitat de resultats, esquemes de solució, conflictes i incertesa, i s’ha pres la qualificació d’experts de les tres organitzacions, els quals indiquen en els individus qualificats el percentatge de temps que dediquen per realitzar cada tipus de tasca en la seva rutina normal. La intensitat de la interacció de xarxes i la propensió a l’IC s’obtenen de les enquestes. De l’anàlisi efectuada, s’observa una relació directa entre la complexitat de tasques i la intensitat en la interacció de la xarxa social de coneixement, com també entre la complexitat i la propensió a intercanviar coneixement. Així mateix, s’ha trobat una relació directa entre les persones que tenen un grau més alt d’interacció en la xarxa social de coneixement i la seva propensió a l’intercanvi de coneixements. Les contribucions principals d’aquesta recerca són aquestes: 1) en l’aspecte acadèmic, la metodologia plantejada quan es treballa amb la qualificació de la persona que coneix millor la naturalesa del treball; 2) en l’aspecte pràctic, la sistematització que es pot obtenir per identificar les persones que tenen més propensió a intercanviar coneixements per potenciar-los dins de l’organització. / El presente trabajo de investigación enfoca uno de los procesos más relevantes de las personas, el Intercambio de Conocimientos (IC). El conocimiento puede ser explícito o tácito. El explícito se puede codificar, estructurar y almacenar de manera que pueda estar disponible. El conocimiento tácito, o también conocido como Tacit Knowing, es la acción de conocer que no se puede codificar ni estructurar; este depende de las experiencias, el criterio y los valores de la persona. Las redes sociales informales en las organizaciones se convierten en un medio por el cual se puede facilitar la transmisión del Tacit Knowing, por lo que mediante el análisis de redes sociales (Social Network Analysis (SNA)) se puede entender y analizar las relaciones entre las personas más allá de las estructuras formales y jerárquicas. Esta situación es relevante para que la alta gerencia potencie, y no trate de estructurar o controlar, estas redes sociales y con una adecuada gestión que incentive que el conocimiento fluya a través de ellas. Se plantean los siguientes objetivos: 1) establecer el Impacto de la Complejidad de Tareas en la intensidad de la interacción de Redes Sociales en una organización, 2) establecer el Impacto de la Complejidad de Tareas en el proceso de Intercambio de Conocimiento y 3) verificar si existe alguna relación entre la intensidad de la interacción de las redes sociales en el proceso de Intercambio de Conocimiento (IC). En la investigación se ha aplicado una encuesta a tres organizaciones peruanas intensivas en conocimiento. Se plantea que a mayor complejidad de tareas, la propensión que debe de tener la persona al intercambio de conocimientos debe ser mayor. Los criterios de clasificación para la complejidad se basan en la multiplicidad de resultados, esquemas de solución, conflictos e incertidumbre y se ha tomado la calificación de expertos de las tres organizaciones, quienes indican en los individuos calificados el porcentaje de tiempo de cada tipo de tareas realizadas en su rutina normal. La intensidad de la interacción de redes y la propensión al IC se obtienen de las encuestas. Del análisis efectuado, se observa una relación directa entre la complejidad de tareas y la intensidad en la interacción de la red social de conocimiento, así como entre la complejidad y la propensión a intercambiar conocimiento. Asimismo, se ha encontrado una relación directa entre las personas que tienen un mayor grado interacción en la red social de conocimiento y su propensión al intercambio de conocimientos. Las principales contribuciones de la presente investigación son las siguientes: 1) en el aspecto académico está la metodología planteada cuando se trabaja con la calificación de la persona que mejor conoce la naturaleza del trabajo; 2) en el aspecto práctico está en la sistematización que se puede obtener para identificar a las personas que tienen una mayor propensión a intercambiar conocimiento para potenciarlos dentro de la organización. / The research addresses one of the most important processes of people, the Knowledge Sharing (KS). Knowledge can be explicit or tacit. The explicit can be structured and stored in a manner that may be available. Tacit knowledge, or also known as Tacit Knowing, is action learning that can not be encoded or structure, this depends on the experience, judgment and values of the person. Informal social networks in organizations become a means to facilitate the transmission of Tacit Knowing, so by analyzing social networks (Social Network Analysis (SNA)) can be understood and analyzed the relationships between people beyond formal and hierarchical structures. This situation is relevant to senior management in order to enhance, rather than try to structure or control, these social networks. An appropriate management should incentive that knowledge flows through them. The research objectives are: 1) establish the Impact of Task Complexity in the intensity of the interaction of social networks in an organization, 2) set the Impact of Task Complexity in the process of knowledge sharing and 3) verify if there is any relationship between the intensity of the interaction of social networks in the process of Knowledge Sharing (KS). A survey has been applied to three peruvian knowledge intensive organizations. It argues that a more complex task, the propensity that the person must have knowledge sharing should be higher. The classification criteria for complexity based on the multiplicity of outcomes, settlement schemes, conflict and uncertainty and has taken the qualification of experts from the three organizations, who qualified individuals listed in the percentage of time each type of task made in their normal routine. The intensity of the interaction of networks and the propensity to KS are obtained from surveys. The analysis conducted, there is a direct relation between task complexity and intensity in the interaction of the social network of knowledge and between complexity and propensity to share knowledge. Also found a direct relationship between people with greater social interaction network of knowledge and their propensity to knowledge sharing. The main contributions of this research are: 1) academically the proposed methodology when working with the qualification of the person who best knows the nature of work, 2) on the practical aspect is that the systematization can get to identify people who have a greater propensity to share knowledge to empower them within the organization.

Community detection in networks is an important area of current research with many applications. Finding community structures is a challenging task and despite significant effort no satisfactory method has been found. Different methods find different communities in the same network and with different computational requirements. To counter this problem, several different methods are often used and the results compared manually. In this thesis, we present three different methods to instead merge the results from different methods (or several runs from the same algorithm) to find better estimates of the community structure. Another problem in practical applications is noisy and imperfect networks with missing and false edges. These imperfections are natural results from the methods used to map the network structure and are often difficult to eliminate. In this thesis, we apply a Monte Carlo-sampling method in combination with the introduced methods for merging community detection results to find community structures in such networks. The method is tested by simulation studies on both real-world networks and synthetic networks with generated uncertainties and imperfections. We finally demonstrate how it is possible to generate confidence levels of the obtained community structure from the merging methods. This allows for a qualitative comparison of the robustness and significance of the network clustering. / Identifikation av grupperingar i nätverk är ett viktigt område inom aktuell forskning med många olika tillämpningsområden. Att finna grupperingar är ofta svårt och trots betydande ansträngningar har ingen tillfredsställande metod hittats. Olika metoder finner ofta olika grupperingar i samma nätverk och kräver varierande beräkningskraft. För att hantera dessa problem används ofta flera metoder vartefter resultaten jämförs manuellt. I detta examensarbete presenterar vi tre olika metoder att istället slå samman resultat från olika metoder (eller fler körningar från samma algoritm) för att hitta bättre uppskattningar av grupperingarna. Ett annat problem i praktiska tillämpningar är brus och ofullständiga nätverk med saknade och falska kanter. Dessa brister är naturliga resultat från de metoder som används för att kartlägga nätverketstrukturen och det är ofta svåra att eliminera dessa. I detta examensarbete använder vi Monte Carlo-metoder i kombination med de introducerade metoderna för att slå samman funna grupperingar för att hitta grupperingar i det osäkra nätverket. Vi testar metoden genom simuleringstudier på både verkliga och syntetiska nätverk med genererade osäkerheter och brister. Slutligen demostrerar vi hur det är möjligt att skapa konfidensnivåer för noder i grupperingar med hjälp av metoderna för sammanslagning. Detta möjliggör en kvalitativ jämförelse av stabilitet och signifikans av identifierade nätverksgrupperingar.

This thesis concerns Social Network Analysis as a mechanism for exploring Community Dynamics. To be able to use the Social Network methodologies, relationships existing between the modeling entities are required. In this thesis, we use two different kinds of relationships: e-mails exchanged and co-authorship of papers. The e-mails exchanged, as an indicator of information exchange in an organization, is used to facilitate the emergence of structure within the organization. In this thesis we demonstrate the effectiveness of using e-mail communication patterns for crisis detection in a hierarchically set organization. We compare the performance of a Social Network based Classifier with some of the traditional classifiers from the data mining framework for inferring this hierarchy. A generic framework for studying dynamic group transformations is presented and the co-authorship of papers, as an indicator of collaboration in an academic institution, is used to study the community behavioral patterns evolving over time. Enron e-mail corpus and the IISc Co-authorship Dataset are utilized for illustrative purposes.

Social media services and applications enable billions of users to share an unprecedented amount of social information, which is further augmented by location and collocation information from mobile phones, and can be aggregated to provide an accurate digital representation of the social world. This dissertation argues that extracted social knowledge from this wealth of information can be embedded in the design of novel distributed, socially-aware applications and services, consequently improving system response time, availability and resilience to attacks, and reducing system overhead. To support this thesis, two research avenues are explored. First, this dissertation presents Prometheus, a socially-aware peer-to-peer service that collects social information from multiple sources, maintains it in a decentralized fashion on user-contributed nodes, and exposes it to applications through an interface that implements non-trivial social inferences. The system's socially-aware design leads to multiple system improvements: 1) it increases service availability by allowing users to manage their social information via socially-trusted peers, 2) it improves social inference performance and reduces message overhead by exploiting naturally-formed social groups, and 3) it reduces the opportunity of attackers to influence application requests. These performance improvements are assessed via simulations and a prototype deployment on a local cluster and on a worldwide testbed (PlanetLab) under emulated application workloads. Second, this dissertation defines the projection graph, the result of decentralizing a social graph onto a peer-to-peer system such as Prometheus, and studies the system's network properties and how they can be used to design more efficient socially-aware distributed applications and services. In particular: 1) it analytically formulates the relation between centrality metrics such as degree centrality, node betweenness centrality, and edge betweenness centrality in the social graph and in the emerging projection graph, 2) it experimentally demonstrates on real networks that for small groups of users mapped on peers, there is high association of social and projection graph properties, 3) it shows how these properties of the (dynamic) projection graph can be accurately inferred from the properties of the (slower changing) social graph, and 4) it demonstrates with two search application scenarios the usability of the projection graph in designing social search applications and unstructured P2P overlays. These research results lead to the formulation of lessons applicable to the design of socially-aware applications and distributed systems for improved application performance such as social search, data dissemination, data placement and caching, as well as for reduced system communication overhead and increased system resilience to attacks.

This research investigates the impact of organizations' collaboration strategies and network positional variables on invention performance. Organizations, particularly those pursuing a differentiation strategy, are motivated to introduce novel products and services in order to remain competitive. Thus, two questions of interest to such organizations regarding the network dynamics of the invention process are: 1) What kind of strategies allow them to attain superior invention results? 2) What is the most advantageous structural positioning in a collaborative network of innovators? Three independent studies attempt to find answers to these questions by using three complementary study approaches. In the first study, in order to examine invention performance of organizations with different collaboration strategies, a simulation model is constructed and run at various levels of technological dynamism and with various types of invention tasks. The cognitive cooperation strategy, which pursues technological knowledge integration as a priority, is found to be the most effective strategy in most experiments. Success-driven cooperators, whose priority is to collaborate with the most effective performers in the network, provided the most consistent invention performance. Moreover, different strategies are shown to perform best at certain points of the industry environment space spanned by technological dynamism and invention type. The second study investigates the impact of positional metrics in a collaboration network on the inventive performance of organizations (as measured by the number of patents issued) by using survey data. Twenty-eight high-tech companies and universities located in Florida are surveyed to reveal their collaborative networking map. Network structural measures are obtained in order to test the hypotheses that high values in centrality metrics correspond with higher inventive performance. The regression analyses imply that degree and closeness centralities are predictive indicators of high inventive performance but the data does not support the significance of impact of local clustering. The third study analyzes the impact of positional metrics on inventive performance by using a national database for the announced research and production joint ventures. From the most inventive organizations (in terms of patent counts) 63 of them are selected for analysis. 371 research and production joint ventures are analyzed to identify their relationship network every year from 1994 to 2012. The results indicate that the number of joint venture partners, being close to other members of the network through network connections and strong local connectivity (except for their interaction effect) is associated with higher invention performance. All three studies bring new methodological contributions to the area of invention network research. The simulation study offers a new model in the area of collaborative invention networks. Furthermore, the ideas and practices developed during the construction of the agent based simulation model for the invention network can be adapted to similar areas of application. The survey study offers a holistic approach for the definition of connections in the development of invention network map and empirically tests it. The database study longitudinally analyzes the evolution of a highly accurate joint venture network over 19-year period while testing the impact of positional metrics with un-weighted and weighted calculation methods. Solutions to our health problems, communication or transportation needs etc. are not usually found due to some series of fortunate events. They are the product of an effective recombination process of technological knowledge. Moreover, effective invention performance is not only important for organizations individually, it is crucial for governments that are concerned with the problems of its citizens. Effective ways of facilitating the recombination of technological knowledge are addressed and presented to inform both companies and policy makers. Better understanding of the dynamics of the invention process will bring more solutions to existing problems.

This study of the motivation to learn English as L2 (as a second/foreign language) provides a local model of L2 motivation which employs a new contextualised perspective. It is based on the socio-cultural backgrounds of the learners and their social relations. This model not only incorporates insights from major debates in the field, but it is also in harmony with recent trends of L2 motivation research. The study had three major objectives. First, it sought to identify the factors that represent Omani students’ motivation to learn English in Oman. Second, it attempted to verify the effects of social relations on motivation. Third, it examined the mechanisms employed by the learners which influence their motivation through personal relations. Since this study views motivation as a complex bundle of constructs, it was more feasible to adopt its most significant factors as determined by the immediate socio-cultural context. Interest and Self-efficacy (SE) were established as the two main constructs representing Omani students’ motivation to learn English as L2. The ‘L2 Motivation Osmosis Model’ was suggested to offer an explanation of the workings of influence on students’ L2 motivation in Oman. This study employed a mixed methodology. A quantitative method was used to confirm the importance of Interest and SE for Omani students. A qualitative study was then designed to further verify this and ascertain the devices employed to influence learners’ motivation. The first question was answered using quantitative and qualitative data. Correlation and Linear Regression statistics were used to verify the importance of Interest and SE. This question was also examined through the students’ depictions of motivated English as L2 learners and the reasons they provided for liking English and why people in Oman learn it. The second question inspected the role of social relations in influencing students’ motivation. The third question studied the devices used by people which influence students’ motivation. The analysis also revealed the importance of the affective dimension expressed through the concept of ‘closeness’, which explains the type and strength of the influence initiated through social relations. This study emphasised the need to consider the socio-cultural context of learners in designing programs and recruiting teachers and the necessity of providing help, encouragement and emotional support. Instead of simply giving recommendations of good practice, the findings of this study provide practitioners with guidelines on how to devise their own plans and guiding principles.

Irregular algorithms such as graph algorithms, sorting, and sparse matrix multiplication, present numerous programming challenges, including scalability, load balancing, and efficient memory utilization. In this age of Big Data we face additional challenges since the data is often streaming at a high velocity and we wish to make near real-time decisions for real-world events. For instance, we may wish to track Twitter for the pandemic spread of a virus. Analyzing such data sets requires combing algorithmic optimizations and utilization of massively multithreaded architectures, accelerator such as GPUs, and distributed systems. My research focuses upon designing new analytics and algorithms for the continuous monitoring of dynamic social networks. Achieving high performance computing for irregular algorithms such as Social Network Analysis (SNA) is challenging as the instruction flow is highly data dependent and requires domain expertise. The rapid changes in the underlying network necessitates understanding real-world graph properties such as the small world property, shrinking network diameter, power law distribution of edges, and the rate at which updates occur. These properties, with respect to a given analytic, can help design load-balancing techniques, avoid wasteful (redundant) computations, and create streaming algorithms. In the course of my research I have considered several parallel programming paradigms for a wide range systems of multithreaded platforms: x86, NVIDIA's CUDA, Cray XMT2, SSE-SIMD, and Plurality's HyperCore. These unique programming models require examination of the parallel programming at multiple levels: algorithmic design, cache efficiency, fine-grain parallelism, memory bandwidths, data management, load balancing, scheduling, control flow models and more. This thesis deals with these issues and more.

This research sought to explore the patterns of co-authorship collaboration between African and international authors who have published together in journals relating to the field of social psychology. Bibliographic data was used to extract and produce social network maps of academic co-author collaborations in which one of the authors was African or affiliated to an author from an African country. These patterns of collaboration were analysed using social network analysis and it was found that, on average, African authors are poorly interconnected with other international authors in the field of social psychology and are also poorly interconnected with other African authors across the continent. It is likely that these structures of collaboration constrain the ability of African authors to produce their own relevant knowledge within the field of social psychology, in that their collaborations are limited and usually mediated by international connections. This pattern of interconnection makes it more likely that African social psychologists will operate within paradigms generated by academics in international and well-resourced countries and militates against the development of African paradigms. / Thesis (M.Soc.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2014.

Il presente lavoro, articolato in due studi etnografici, intende contribuire allo sviluppo del Modello dell’Intersoggettività Enunciativa, considerando aspetti fino a questo momento esclusi dallo stesso. L’aspetto caratterizzante degli studi riguarda l’utilizzo di videoregistrazioni delle osservazioni etnografiche, utilizzate con obiettivi diversi. Nel primo caso sono prodotte in ottica di Etnografia Focalizzata, come supporto all’osservazione, mentre nel secondo sono utilizzate per effettuare ulteriori analisi a partire da quanto emerso dalla prima fase qualitativa. Il primo è stato uno studio di etnografia focalizzata su un progetto pilota di educazione digitale per users non nativi digitali, all’interno del quale si è riscontrato come il device risulti di ostacolo alla collaborazione tra gli individui, in quanto essi non possiedono le conoscenze e competenze necessarie a favorirla. Diversamente, nel secondo studio è stato utilizzata la Social Network Analysis, con l’obiettivo di comprendere le modalità di interazione costituite all’interno di gruppi di studenti che lavorano in presenza, ai fini di un obiettivo comune, con il supporto di device mobili. Dai risultati emerge come il dispositivo mobile funzioni ai fini della costruzione del mondo intersoggettivo condiviso solo se trasparente, evidenziando la necessità di considerare imprescindibile l’uso quotidiano e trasparente di tali tecnologie per tutte le fasce di popolazione. / This work, organized into two ethnographical studies, aims at contributing to the development of the Utterance Intersubjectivity model considering aspects not yet included in such model. The performed studies entail the use of videorecordings of ethnographic observations in multiple settings. In the first case, they are produced with a Focused Ethnography purpose in support to the observation, in the second case they are used after a preliminary qualitative step to perform an additional set of analyses. The first study is a focused ethnography on a pilot project considering digital training for non digital-native users. The main outcome is the insight that the device results to be an impairment to the individuals collaboration, since they do not possess the required minimum level of knowledge and competence. In the second study a Social Network Analysis approach is used, with the objective to understand the interaction modalities that emerge within groups of co-located students working towards a common objective with the support of mobile devices. Comparing the results of the studies emerges that mobile devices are effective in the construction of the shared intersubjective world only if they are transparent to the users, highlighting the need to promote and reinforce the everyday use of such technologies.

Objective: To understand the use of evidence-informed decision-making within an interorganizational network, and identify the facilitators and barriers to achieving network goals. Design: Case study. Setting: Rural health district in Nova Scotia, Canada (2006 to 2011). Participants: Members from 4 organizations representing community and hospital groups participating in a regional Baby Friendly Initiative network. Methods: A descriptive mixed methods study using focus group and questionnaire methodology. Data were analyzed using framework analysis and social network analysis (SNA). Results: The SNA results highlighted the role that relationships have on the sharing of knowledge among network members. The findings highlight the need for leadership at multiple levels (community, network members, primary organizations, and the provincial government). A lack of resources to achieve the network’s goals was a key barrier. Conclusions: The role of multi-level leadership is important for future network development and community consideration. The case study methodology facilitated momentum towards the network’s goals.