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Las redes sociales virtuales como Facebook y Twitter están muy difundidas en nuestras vidas cotidianas y generan un montón de datos de intercambios. Planteamos un modelo estocástico para Twitter que nos permite estudiar la dinámica de la red y el comportamiento de los usuarios sobre su saturación. Para estudiar este modelo estocástico se utiliza la herramienta estadística de cópulas que analiza la dependencia de variables aleatorias. Este trabajo de tesis proponemos una generalización del estimador por núcleos de cópulas para serie de tiempos presentado por Fermanian y Scaillet en 2002. Dicha generalización se extiende a procesos estocásticos de difusión. A partir de éste estimador, se puede analizar la probabilidad de saturación de un usuario de Twitter y otras medidas vinculadas con esta saturación. / Virtual social networks like Facebook and Twitter are very spread in daily life. Using it generates an incredible amount of exchange information. In this work we propose an stochastic model for Twitter that allows the study of network dynamics and users behavior specially concern with saturation. To study this model we use a statistical tool named as copulas that analices dependence between random variables. In this thesis we propose a generalization of the non-parametric copula estimator presented by Fermanian and Scaillet in 2002. This generalization reaches continuos process as diffusion. From this estimator we can analize profile saturation probability and other measures related with saturation.

Leadership emergence is best conceptualized as a complex, multi-level process arising from the dynamic interplay of all elements in the process: group members, relations, and context (Day, 2014). This study seeks to simultaneously examine to the role of each in the leadership emergence process by assessing leader and follower traits, their trait similarity, task, behaviors, and the network itself. Using a rotation design, 99 cadets in groups of three completed four tasks with alternating partners and subsequently provided sociometric ratings of each of their group members. Data was analyzed using Exponential Random Graph Modeling, which controls for endogenous group effects. In general, there was a tendency toward nominating others as leaders. High scores on dominance and intelligence predicted leadership emergence, and low scores on dominance predicted follower emergence. The type of task did not affect leadership emergence. Perceived leader behavior unexpectedly reduced the likelihood of nominating another as a leader. Results from this study highlight the importance of studying all components of leadership process and are once step closer toward doing so completely and accurately. / Master of Science

published_or_final_version / Social Work / Master / Master of Social Work

The present study aims to investigate whether online social support could function in the same way as the offline social support to protect our well-being from stress, and to examine how different Internet activities affected Hong Kong adolescents’ online and offline social support, and their subsequent well-being.305 Hong Kong students from grade 10 and 11 participated in the present study. Descriptive statistics found that female adolescents had a higher level of perceived offline social support than male adolescents. Hierarchical multiple regression analyses were conducted to test the buffering effect of both perceived offline and online social support on the relationship between stress and anxiety. Results found that perceived online social support could not buffer stress for Hong Kong adolescents. The buffering effect of perceived offline social support was only found in female adolescents. On the other hand, present results suggested that the actual impact of Internet depended on the types of Internet activities and their corresponding impact on offline and online social support. Implications on the importance of offline social support, gender difference on reactions towards social support and education on Internet usage were discussed. / published_or_final_version / Educational Psychology / Master / Master of Social Sciences

Data dissemination problem is a challenging issue in social networks, especially in mobile social networks, which grows rapidly in recent years worldwide with a significant increasing number of hand-on mobile devices such as smart phones and pads. Short-range radio communications equipped in mobile devices enable mobile users to access their interested contents not only from access points of Internet but also from other mobile users. Through proper data dissemination among mobile users, the bandwidth of the short-range communications can be better utilized and alleviate the stress on the bandwidth of the cellular networks. In this dissertation proposal, data dissemination problem in mobile social networks is studied. Before data dissemination emerges in the research of mobile social networks, routing protocol of finding efficient routing path in mobile social networks was the focus, which later became the pavement for the study of the efficient data dissemination. Data dissemination priorities on packet dissemination from multiple sources to multiple destinations while routing protocol simply focus on finding routing path between two ends in the networks. The first works in the literature of data dissemination problem were based on the modification and improvement of routing protocols in mobile social networks. Therefore, we first studied and proposed a prediction-based routing protocol in delay tolerant networks. Delay tolerant network appears earlier than mobile social networks. With respect to delay tolerant networks, mobile social networks also consider social patterns as well as mobility patterns. In our work, we simply come up with the prediction-based routing protocol through analysis of user mobility patterns. We can also apply our proposed protocol in mobile social networks. Secondly, in literature, efficient data dissemination schemes are proposed to improve the data dissemination ratio and with reasonable overhead in the networks. However, the overhead may be not well controlled in the existing works. A social-aware data dissemination scheme is proposed in this dissertation proposal to study efficient data dissemination problem with controlled overhead in mobile social networks. The data dissemination scheme is based on the study on both mobility patterns and social patterns of mobile social networks. Thirdly, in real world cases, an efficient data dissemination in mobile social networks can never be realized if mobile users are selfish, which is true unfortunately in fact. Therefore, how to strengthen nodal cooperation for data dissemination is studied and a credit-based incentive data dissemination protocol is also proposed in this dissertation. Data dissemination problem was primarily researched on mobile social networks. When consider large social networks like online social networks, another similar problem was researched, namely, information diffusion problem. One specific problem is influence maximization problem in online social networks, which maximize the result of information diffusion process. In this dissertation proposal, we proposed a new information diffusion model, namely, sustaining cascading (SC) model to study the influence maximization problem and based on the SC model, we further plan our research work on the information diffusion problem aiming at minimizing the influence diffusion time with subject to an estimated influence coverage.

University of Macau / Faculty of Science and Technology. / Department of Computer and Information Science