Orientadora: Maria do Rosário Gomes Lima da Silva / Banca: Daniela Nogueira de Moraes Garcia / Banca: Telma de Souza Garcia Grande / Resumo: Este trabalho visa apresentar as potencialidades do uso das redes sociais, especificamente o Facebook, como recurso didático-pedagógico nas aulas de Língua Portuguesa para promoção de habilidades da leitura e da escrita por meio do acesso e produção de gêneros textuais/digitais que permeiam esse espaço virtual. Inicialmente, realizou-se uma investigação sobre tecnologias na educação, tomando-se por base teóricos e especialistas no assunto, com o objetivo de promover uma reflexão sobre o uso pedagógico das redes sociais na educação. As atividades foram desenvolvidas com alunos das Séries Finais do Ensino Fundamental, de uma escola estadual no interior do estado de São Paulo, considerando a importância de se adquirir, na sociedade contemporânea, conhecimentos e habilidades para participação em práticas sociais em ambientes digitais. Nesse contexto, a proposta foi verificar o desenvolvimento do letramento digital, considerando-se que são internautas ainda em formação escolar e dominam as tecnologias atuais que estão incorporadas no seu cotidiano. Cabe mencionar que várias pesquisas realizadas no campo da educação apontam para as dificuldades relacionadas à deficiência da leitura, da escrita, que abrangem uma parcela significativa destes alunos. No entanto, acredita-se que nunca se leu e se escreveu tanto como nos dias atuais graças à repercussão dos espaços digitais, é inegável a necessidade da utilização dos meios tecnológicos no ambiente escolar. Assim, por meio do uso de tecnologia na educação, pretende-se contribuir na formação desses jovens enquanto cidadãos, e também na construção de novos conhecimentos e, consequentemente, na ampliação dos horizontes visando à formação de estudantes multiletrados / Abstract: The objective of this paper is to present the possibilities of using social media, Facebook, to be more specific, as a pedagogical and didactic tool in Portuguese language classes for the 9th grade to develop reading and writing skills by reading and writing different text/digital genres that are found in this media. In order to do so, firstly we researched about Educational technologies by surveying and reflecting about the pedagogical uses of social media. Activities were developed with 9th grade students in a state school inland São Paulo state who are native computer users dealing well with technology, but still in formal education and need to take part in social practices. Several researches in Education point out that there are difficulties towards reading and writing with basic education students. However thanks to digital spaces, students have never read and written so much. So, we cannot deny the need of using technology in schooling. By using it, we intend to help students to become citizens, to build new knowledge and hence, to broad horizons by forming multi literate students / Mestre

A growing body of research suggests that intra-organizational mobility represents an important source of value creation and retention. Internal hires who are embedded in organizational social networks have greater resources and experience than external workers who are less socially connected. Notwithstanding the great practical and theoretical interest in the benefits of intra-organizational mobility at the organizational level, little is known about how individuals’ intra-organizational careers unfold and the influence of social networks toward that end. This dissertation combines findings from three separate projects to investigate the mechanisms underlying the phenomenon of intra-organizational mobility—the structural factors that explain why people move within an organization, how movers and incumbents do or do not benefit from mobility, and the individual differences in network behavior for mobility. More specifically, in the first chapter, I examine how pre-existing communication contacts affect the mover’s performance upon joining the new group. I expect that movers are more likely to join business units to which they have pre-existing ties. Nonetheless, the ties that facilitate movers’ joining business units are oftentimes not those that help them to perform well subsequently. In the next chapter, I explore gender differences in network behavior as they impact on intra-organizational mobility. I argue that when a mover retains ties to the working unit that is being left, it improves the mover’s post-move performance. And women are more likely to maintain such persistent social ties, whereas men are more likely to establish new ties. In the final chapter, I assess the effects on the receiving group when a mover joins, and I argue that low-ranking incumbents embedded in stable performance hierarchies suffer from the introduction of high-performing newcomers and the induced unfavorable social comparison. I test my predictions using time-series data on the internal inter-branch transfers of retail sales employees at a US-based financial institution between November 2014 and April 2016. The dataset is composed of individual demographic information, monthly performance metrics (in dollars), and meta email communication among all employees. The data permits several methodological advancements: (1) the use of objective and consistent performance measures; (2) analysis of the temporal changes in the networks of the movers and their contacts; (3) analysis of communication network and its impact on performance, and (4) robustness checks that apply instrumental variable techniques. The approach taken in this dissertation adds a new perspective on the relationship between intra-organizational mobility and competitive advantage.

abstract: The popularity of social media has generated abundant large-scale social networks, which advances research on network analytics. Good representations of nodes in a network can facilitate many network mining tasks. The goal of network representation learning (network embedding) is to learn low-dimensional vector representations of social network nodes that capture certain properties of the networks. With the learned node representations, machine learning and data mining algorithms can be applied for network mining tasks such as link prediction and node classification. Because of its ability to learn good node representations, network representation learning is attracting increasing attention and various network embedding algorithms are proposed. Despite the success of these network embedding methods, the majority of them are dedicated to static plain networks, i.e., networks with fixed nodes and links only; while in social media, networks can present in various formats, such as attributed networks, signed networks, dynamic networks and heterogeneous networks. These social networks contain abundant rich information to alleviate the network sparsity problem and can help learn a better network representation; while plain network embedding approaches cannot tackle such networks. For example, signed social networks can have both positive and negative links. Recent study on signed networks shows that negative links have added value in addition to positive links for many tasks such as link prediction and node classification. However, the existence of negative links challenges the principles used for plain network embedding. Thus, it is important to study signed network embedding. Furthermore, social networks can be dynamic, where new nodes and links can be introduced anytime. Dynamic networks can reveal the concept drift of a user and require efficiently updating the representation when new links or users are introduced. However, static network embedding algorithms cannot deal with dynamic networks. Therefore, it is important and challenging to propose novel algorithms for tackling different types of social networks. In this dissertation, we investigate network representation learning in social media. In particular, we study representative social networks, which includes attributed network, signed networks, dynamic networks and document networks. We propose novel frameworks to tackle the challenges of these networks and learn representations that not only capture the network structure but also the unique properties of these social networks. / Dissertation/Thesis / Doctoral Dissertation Computer Science 2018

This thesis develops and tests a social network theory of religion to explain the phenomena of religious and secular beliefs in the general population in contemporary Britain. Drawing upon the writings of several historians and upon the work of Giddens (1994a, 1994b), the study is placed in the theoretical context of the debate about the nature of modernity. Due to the various processes of modernization it is argued that personal network links between church attenders and non-church attenders have gradually been severed since pre-modern times. The immediate consequences of this development are twofold. First, the transmission of church religion is greatly restricted. Second, personal overarching religious, or indeed secular, world views are now likely to be formulated, maintained, modified and transmitted by individuals within discrete and geographically dispersed social networks within the private sphere. On the basis of this argument a network dependency hypothesis was formulated, from which twenty-two testable propositions were derived. By employing ego-centred network analysis, the empirical dimension of this thesis reports the testing of each of these propositions against data obtained from a quantitative 500 questionnaire survey of a middle class suburb in the south of England, followed by 39 qualitative focused interviews with informants selected from the initial survey. The data showed that responses to the process of primary socialization had a profound effect on the initial belief formation of ego. This provided a foundation both for religious or secular belief in later life and for the future selection of network alters. With the exception of conversionists, these beliefs generally continued to be maintained by ego within ego's current network. At all stages ego demonstrated a need to reduce cognitive dissonance and to pursue cognitive consonance (Festinger, 1985). The local community did not constitute a plausibility structure and even the local church did not perform this function. Only discrete, dispersed, personal networks in the private sphere functioned to maintain the plausibility of religious and secular beliefs. The findings constituted overwhelming support for the network dependency hypothesis.

Users face location-privacy risks when accessing Location-Based Services (LBSs) in an Opportunistic Mobile Social Networks (OMSNs). In order to protect the original requester's identity and location, we propose two location privacy obfuscation protocols utilizing social ties between users. The first one is called Multi-Hop Location-Privacy Protection (MHLPP) protocol. To increase chances of completing obfuscation operations, users detect and make contacts with one-hop or multi-hop neighbor friends in social networks. Encrypted obfuscation queries avoid users learning important information especially the original requester's identity and location except for trusted users. Simulation results show that our protocol can give a higher query success ratio compared to its existing counterpart. The second protocol is called Appointment Card Protocol (ACP). To facilitate the obfuscation operations of queries, we introduce the concept called Appointment Card (AC). The original requesters can send their queries to the LBS directly using the information in the AC, ensuring that the original requester is not detected by the LBS. Also, a path for reply message is kept when the query is sent, to help reduce time for replying queries. Simulation results show that our protocol preserves location privacy and has a higher query success ratio than its counterparts. We have also developed a new OMSN simulator, called OMSN Routing Simulator (ORS), for simulating OMSN protocols more efficiently and effectively for reliable performance.

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Magister Philosophiae (Land and Agrarian Studies) - MPhil(LAS) / Following Bryceson's article, 'De-agrarianisation in Sub-Saharan Africa: Acknowledging the Inevitable', and other related writings in the volume Farewell to Farms, rural development has become a contested academic and policy domain. One side of the debate is characterized by 'agrarian optimism', mirrored in various state policies and advice from the World Bank; the other side is typified by the de-agrarianisation thesis, which is sceptical regarding the agrarian path to rural development, because it doesn't accord with dominant trends. The main reasons given for the trend of de-agrarianisation are: unfavourable climatic trends, economic adjustments, and population growth. While the de-agrarianisation thesis seems to be a sensible proposition, it has failed to attract many disciples, evidenced by the continuation of current policy directions towards the agrarian optimistic path. The purpose of this study was to assess the applicability of the de-agrarianisation thesis in the Gokwe-Kabiyuni area of Zimbabwe, during a time when the nation went through climatic, economic and political crises. The idea was to assess the influence of such an environment to smallholder farmers in terms of livelihood strategies by observing trends in climate, education, occupation, and crop yields over the period. Both qualitative and quantitative methods were used to establish whether the de-agrarianisation process can be noted in two villages over the period 1990-2008. A comparative analysis of the experiences of smallholder farmers in these two villages revealed the existence of a cultivation culture and differential agrarian resilience depending on natural resource endowment and levels of infrastructural development, notwithstanding the involvement of the villagers in non-farm activities to diversify their livelihood portfolios. / South Africa

Philosophiae Doctor - PhD / Adaptive networks are complex networks with nontrivial topological features and connection patterns between their elements which are neither purely regular nor purely random. Their applications are in sociology, biology, physics, genetics, epidemiology, chemistry, ecology, materials science, the traditional Internet and the emerging Internet of-Things. For example, their applications in sociology include social networks such as Facebook which have recently raised the interest of the research community. These networks may hide patterns which, when revealed, can be of great interest in many practical applications. While the current adaptive network models remain mostly theoretical and conceptual, however, there is currently no unified modelling framework for implementing the development, comparison, communication and validation of agent-based adaptive network models through using proper empirical data and computation models from different research fields. In this thesis, a unified framework has been developed that combines agent- based adaptive network models and adaptive control structures. In this framework, the control parameters of adaptive network models are included as a part of the state- topology coevolution and are automatically adjusted according to the observations obtained from the system being studied. This allows the automatic generation of enhanced adaptive networks by systematically adjusting both the network topology and the control parameters at the same time to accurately reflect the real-world complex system. We develop three different applications within the general framework for agent- based adaptive network modelling and simulation of real-world complex systems in different research fields. First, a unified framework which combines adaptive net- work models and adaptive control structures is proposed for modelling and simulation of fractured-rock aquifer systems. Moreover, we use this unified modelling framework to develop an automatic modelling tool, Fracture3D, for automatically building enhanced fracture adaptive network models of fractured-rock aquifer systems, in which the fracture statistics and the structural properties can both follow the observed statistics from natural fracture networks. We show that the coupling between the fracture adaptive network models and the adaptive control structures with iterative parameter identification can drive the network topology towards a desired state by dynamically updating the geometrical states of fractures with a proper adaptive control structure. Second, we develop a unified framework which combines adaptive network models and multiple model adaptive control structures for modelling and simulation of social network systems. By using such a unified modelling framework, an automatic modelling tool, SMRI, is developed for automatically building the enhanced social adaptive network models through using mobile-phone-centric multimodal data with suitable computational models of behavioural state update and social interaction update. We show that the coupling between the social adaptive network models and the multiple model adaptive control structures can drive the community structure of a social adaptive network models towards a desired state through using the suitable computational models of behavioural state update and social interaction update predetermined by the multiple model adaptive control structure. Third, we develop a unified framework which combines adaptive network models and support vector machine based adaptive control structures for modelling and simulation of multicast congestion in mobile ad hoc network systems. Moreover, a multicast congestion detection scheme, WMCD, has been developed for the unified modelling framework, in which the incipient congestions of group members can be predicted by using support vector machine-based prediction models and current traffic states. We show that the network’s throughput capacity is efficiently improved through using the unified modelling framework, which dynamically adjusting the group structures according to the updated congestion states of group members generated by the WMCD scheme in order to relieve the high load.

This diploma thesis aims at main methods of fighting against disinformation and propaganda in society. The goal of this thesis was to find out how the European Union tackles the problem at the level of its three main institutions and how the Czech and the Slovak Republic combat false news and propaganda at the government and state bodies level, at civil society level, and at the level of the media. The thesis consists of four chapters. The first two chapters describe the theoretical framework of communication, differentiate different types of information, and describe the practical determination of disinformation. The third chapter aims at analysis of access of the institutions of the European Union to the problem of disinformation in the society and on the internet. The fourth chapter introduces the results of a survey conducted on the above mentioned levels in the Czech Republic and in Slovakia. In the final part, the access of both countries and the European Union is evaluated by a comparative analysis method.

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