In this thesis we study the impact of time in the analysis of social networks. To do that we represent a knowledge mobilization network, Knowledge-Net, both as a standard static graph and a time-varying graph and study both graphs to see their differences. For our study, we implemented some temporal metrics and added them to Gephi, an open source software for graph and network analysis which already contains some static metrics. Then we used that software to obtain our results. Knowledge-Net is a network built using the knowledge mobilization concept. In social science, knowledge mobilization is defined as the use of knowledge towards the achievement of goals. The networks which are built using the knowledge mobilization concept make more visible the relations among heterogeneous human and non-human individuals, organizational actors and non-human mobilization actors. A time-varying graph is a graph with nodes and edges appearing and disappearing over time. A journey in a time-varying graph is equivalent to a path in a static graph. The notion of shortest path in a static graph has three variations in a time-varying graph: the shortest journey is the journey with the least number of temporal hops, the fastest journey is the journey that takes the least amount of time and the foremost journey is the journey that arrives the soonest. Out of those three, we focus on the foremost journey for our analysis.

Made available in DSpace on 2014-12-17T14:56:17Z (GMT). No. of bitstreams: 1 EdsonAMRB_DISSERT.pdf: 7502344 bytes, checksum: 78d70443ae2fd9033fe78b23c5cbd811 (MD5) Previous issue date: 2013-07-30 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior / Complex network analysis is a powerful tool into research of complex systems like brain networks. This work aims to describe the topological changes in neural functional connectivity networks of neocortex and hippocampus during slow-wave sleep (SWS) in animals submited to a novel experience exposure. Slow-wave sleep is an important sleep stage where occurs reverberations of electrical activities patterns of wakeness, playing a fundamental role in memory consolidation. Although its importance there s a lack of studies that characterize the topological dynamical of functional connectivity networks during that sleep stage. There s no studies that describe the topological modifications that novel exposure leads to this networks. We have observed that several topological properties have been modified after novel exposure and this modification remains for a long time. Major part of this changes in topological properties by novel exposure are related to fault tolerance / A an?lise da topologia de redes ? uma poderosa ferramenta no estudo de sistemas complexos tal como as redes cerebrais. Este trabalho procura descrever as mudan?as na topologia de redes de conex?o funcional em neur?nios do c?rtex sensorial e do hipocampo durante o sono de ondas lentas (SWS) em animais expostos ? novidade. O sono de ondas lentas ? um importante estado do sono onde h? reverbera??o de padr?es de atividade el?trica ocorridos na vig?lia, tendo com isso papel fundamental na consolida??o de mem?ria. Apesar de sua import?ncia ainda n?o h? estudos que caracterizam a din?mica da topologia de redes de conex?o funcional durante este estado. Tampouco h? estudos que descrevem as modifica??es topol?gicas que a exposi??o ? novidade traz a essas redes. Observamos que v?rias propriedades topol?gicas s?o modificadas ap?s a exposi??o ? novidade e que tais modifica??es se mant?m por um longo per?odo de tempo. A maior parte das propriedades modificadas pela exposi??o ? novidade est? relacionada ? toler?ncia ? falha