M. Tech. Business Information Systems / The main objective of this study was to develop a framework for the utilization of Web 2.0 tools in teaching and learning in a university of technology. The study was informed by data that was collected quantitatively from the Tshwane University of Technology (TUT). Extensive literature review was conducted and by using content analysis 36 factors were deduced.

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Στην παρούσα εργασία παρουσιάζεται η επίδραση του facebook ως online κοινωνικό δίκτυο στις καταναλωτικές συμπεριφορές του Έλληνα χρήστη του facebook. Αρχικά στο δεύτερο κεφάλαιο παρουσιάζεται, με την βοήθεια της διεθνούς βιβλιογραφίας, ο ορισμός των online κοινωνικών δικτύων. Ύστερα παρουσιάζονται ιστορικά και στατιστικά στοιχεία των online κοινωνικών δικτύων και στη συνέχεια παρουσιάζονται και αναλύονται τα πιο χρήσιμα εργαλεία του μάρκετινγκ στις νέες τεχνολογίες (eWOM, viral, direct marketing). Ακολουθεί, στο τρίτο κεφάλαιο, η παρουσίαση της μεθοδολογίας της έρευνας και η ανάλυση του ερευνητικού εργαλείου και της μεθόδου δειγματοληψίας. Στην παρούσα εργασία έγινε χρήση μοντέλων έρευνας ακαδημαϊκά αναγνωρισμένων όπως το TAM & trust. Στο τέταρτο κεφάλαιο γίνεται η ανάλυση δεδομένων ξεκινώντας με την ανάλυση των δημογραφικών χαρακτηριστικών των χρηστών του facebook. Στη συνέχεια γίνεται αξιολόγηση των μετρήσεων και τέλος το profiling των χρηστών. Η ανάλυση των δεδομένων, με την βοήθεια των factor & cluster analysis, έδωσε τρεις ομάδες χρηστών, οι οποίες και αναλύονται διεξοδικά. Στο τελευταίο κεφάλαιο προτείνονται στους αναγνώστες ποια εργαλεία του μάρκετινγκ είναι πιο αποτελεσματικά για κάθε μία από τις ομάδες χρηστών, αναφέρονται οι περιορισμοί και γίνονται προτάσεις για μελλοντικές έρευνες / This paper presents the impact of facebook as an online social network on consumer attitudes of the Greek users of facebook. Initially, in second chapter, it is presented, with the help of the international literature, the definition of online social networks. After is presented a history and statistics of online social networks and then is presented and analyzed the most useful tools of marketing to new technologies (eWOM, viral, direct marketing). Then, in chapter three, it follows the presentation of the research methodology and analysis of the research tool and method of sampling. This work uses research models academically recognized such as the TAM & trust. The fourth chapter constitutes data analysis, starting first with analyzing the demographic characteristics of the users of facebook. Then an evaluation of the measurements takes part and finally the profiling of users. The analysis of data, with the help of factor & cluster analysis, gave three clusters, which were analyzed in detail. In the last chapter is suggested to readers which of the marketing tools are most effective for each of the user groups, limitations are mentioned and recommendations are made for future research

Thesis (MPhil)--Stellenbosch University, 2014. / ENGLISH ABSTRACT: With the emergence of Web 2.0 (social network platforms) some Knowledge Management theorists saw the potential for incorporating its collaborative and networking features in Knowledge Management Systems. However, the consensus is that harnessing Web 2.0 features for Knowledge Management is still in its infancy and according to some it seems that Web 2.0 success in the social sphere is hard to translate to the work context. The thesis argues that Web 2.0 primarily facilitates Personal Knowledge Management (PKM) and in this way indirectly contributes to Organisational Knowledge Management. Furthermore not all Web 2.0 features are equally useful in facilitating Personal Knowledge Management. The thesis identifies the group features of social network platforms as the prime locations for networking and learning. The thesis is theoretically based on Cheong and Tsui's PKM 2.0 model, in particular the Interpersonal Knowledge Transferring phase that in turn is based on Nonaka's SECI model of knowledge conversion. The thesis starts out with considering the distinction and relationship between Organisational Knowledge Management (OKM) and Personal Knowledge Management (PKM). Thereafter Cheong and Tsui's PKM 2.0 model is described as well as Nonaka's SECI model. The Web 2.0 phenomenon is introduced through a literature review of various studies on the usefulness of social network platforms and the group features are specifically highlighted. A survey is conducted among users of a particular Web 2.0 group feature, based on questions developed from the SECI and PKM 2.0 models. The thesis comes to the conclusion that the group features of Web 2.0 social network platforms are useful for Knowledge Management, because it is indeed a component of users' Personal Knowledge Management. / AFRIKAANSE OPSOMMING: Sekere Kennisbestuursteoretici het met die opkoms van Web 2.0 (sosiale netwerk-platforms) die moontlikheid waargeneem om die samewerks- en netwerk-funksionaliteit van Web 2.0 platforms met bestaande Kennisbestuurstelsels te integreer. Die konsensus is egter dat sulke pogings nog veel tekortskiet en sommige waarnemers meen dat dit baie moeilik sal wees om Web 2.0 se sukses in die sosiale sfeer in die werksplek in te span. Die tesis argumenteer dat Web 2.0 hoofsaaklik Persoonlike Kennisbestuur (PKB) fasiliteer en langs hierdie ompad 'n bydrae lewer tot Organisatoriese Kennisbestuur (OKB). Verder lewer alle funksionaliteite van Web 2.0 nie 'n bruikbare bydra tot Kennisbestuur nie, maar is dit hoofsaaklik die groepsfunksies wat bruikbaar is in terme van netwerking en leer. Die tesis is teoreties gewortel in Cheong en Tsui se PKB 2.0 model, veral die Interpersoonlike Kennisoordragsfase wat weer op Nonaka se SEKI model gebaseer is. Die tesis oorweeg aanvanklik die onderskeid en verhouding tussen Organisatoriese Kennisbestuur (OKB) en Persoonlike Kennisbestuur (PKB). Daarna word Cheong en Tsui se PKB 2.0 model en Nonaka se SEKI model bespreek. Die Web 2.0 fenomeen word beskryf aan die hand van 'n literatuurstudie van navorsing oor die bruikbaarheid van Web 2.0 platforms en die groepsfunksionaliteit word spesifiek belig. 'n Vraelys, gebaseer op die SEKI en PKB 2.0 modelle, is onder gebruikers van 'n spesifieke Web 2.0 groepsfunksie geadministreer. Die tesis kom tot die konklusie dat die groepsfunksies van Web 2.0 sosiale netwerk-platforms bruikbaar is vir Kennisbestuur, want dit is inderdaad 'n komponent van gebruikers se Persoonlike Kennisbestuur (PKB).

Notre société doit faire face à de nombreux changements dans les modes de communication.L’émergence simultanée des terminaux nomades et des réseaux sociaux numériques permet désormais de partager des informations depuis presque n’importe quel lieu et potentiellement avec toutes les entités connectées.Le développement de l’usage des smartphones dans un cadre professionnel ainsi que celui des réseaux sociaux numériques constitue une opportunité, mais également une source d’exposition à de nombreuses menaces telles que la fuites d’information sensible, le hameçonnage, l’accès non légitime à des données personnelles, etc.Alors que nous observons une augmentation significative de la malveillance sur les plateformes sociales, aucune solution ne permet d’assurer un usage totalement maîtrisé des réseaux sociaux numériques. L’apport principal de ce travail est la mise en place de la méthodologie (SPOTLIGHT) qui décrit un outil d’analyse comportementale d’un utilisateur de smartphone et de ses contacts sur les différents médias sociaux. La principale hypothèse est que les smartphones, qui sont étroitement liés à leurs propriétaires, mémorisent les activités de l’utilisateur (interactions) et peuvent être utiles pour mieux le protéger sur le numérique.Cette approche est implémentée dans un prototype d’application mobile appelé SPOTLIGHT 1.0 qui permet d’analyser les traces mémorisées dans le smartphone d’un utilisateur afin de l’aider à prendre les décisions adéquates dans le but de protéger ses données / Our society is facing many changes in the way it communicates. The emergence of mobile terminals alongside digital social networks allows information to be shared from almost anywhere with the option of all parties being connected simultaneously. The growing use of smartphones and digital social networks in a professional context presents an opportunity, but it also exposes businesses and users to many threats, such as leakage of sensitive information, spamming, illegal access to personal data, etc.Although a significant increase in malicious activities on social platforms can be observed, currently there is no solution that ensures a completely controlled usage of digital social networks. This work aims to make a major contribution in this area through the implementation of a methodology (SPOTLIGHT) that not only uses the behaviour of profiles for evaluation purposes, but also to protect the user. This methodology relies on the assumption that smartphones, which are closely related to their owners, store and memorise traces of activity (interactions) that can be used to better protect the user online.This approach is implemented in a mobile prototype called SPOTLIGHT 1.0, which analyses traces stored in users’ smartphone to help them make the right decisions to protect their data

Orientador: Prof. Dr. Carlos Alberto Kamienski / Dissertação (mestrado) - Universidade Federal do ABC, Programa de Pós-Graduação em Engenharia da Informação, 2015. / O presente trabalho apresenta uma abordagem de análise da rede social Twitter a fim de entender como os usuários se tornam influentes, através das suas características pessoais e das características dos seus tuítes. As redes sociais online vêm sendo utilizadas, cada vez mais, para análises de diferentes áreas de pesquisa que se propõem a entender como as relações humanas ocorrem e como são estruturadas. Este projeto se propõe a entender como os conteúdos são difundidos no Twitter, quais as características dos usuários denominados influentes, por serem formadores de opinião, e as características das mensagens que se tornaram virais. Entender como as pessoas se comportam em um grupo é um grande desafio. Com este objetivo, foi criado um coletor de dados para capturar tuítes criados em sete temas diferentes e servir como entrada de dados para as análises de influência através de diferentes técnicas, como: contagem de retuítes e menções, entendimento de quais características costumam apresentar os tuítes que alcançam maior disseminação, criação de grafos relacionando usuários, seus seguidores, tuítes e retuítes para aplicar técnicas de redes complexas e análise com mineração de dados utilizando árvore de decisão. A estratégia utilizada foi aplicar diferentes técnicas para comparar os resultados e chegar em um modelo que possa prever quando um conteúdo ou usuário será influente. Ao todo, foram coletados mais de 62 milhões de tuítes entre os anos de 2014 e 2015. Apesar da grande quantidade de dados, não foi possível desenvolver um padrão exato de como um usuário ou conteúdo se torna influente, porém foi possível entender diversas características que estão presentes nesses usuários e que podem ser utilizadas para aumentar o potencial de disseminação de um conteúdo específico. / This paper presents an analitical approach of the social network Twitter in order to understand how its users become influential through their personal characteristics and the characteristics of their tweets. Online social networks have been increasingly used for analysis of different areas of research that intend to understand how human relationships occur and how they are structured. This project aims at understanding how content is spread on Twitter, what the characteristics of users called influential are, for being opinion leaders, and characteristics of messages that have gone viral. Understanding how people behave in a group is a great challenge. For this purpose, a data collector has been created to capture tweets created in seven different themes as well as to serve as input for the analyzes of influence through different techniques, such as, counting retweets and mentions, understanding of what features usually present tweets that reach further spread, creating graphs relating users, followers, tweets and retweets to apply techniques of complex networks and analysis with data mining using decision tree. The strategy used was to apply different techniques to compare results and get a model that can predict when content or user is influential. In all, we collected more than 62 million tweets between the years 2014 and 2015. Despite the large amount of data, it was not possible to develop an accurate standard for how a user or content becomes influential, but it was possible to understand several characteristics that these users are presenting and can be used to increase the potential for dissemination of specific content.

Orientador: Prof. Dr. Carlos Kamienski / Dissertação (mestrado) - Universidade Federal do ABC, Programa de Pós-Graduação em Engenharia da Informação, 2015.

Information gathered socially online is a key feature of the growth and development of modern society. Presently the Internet is a platform for the distribution of data. Millions of people use Online Social Networks daily as a tool to get updated with social, political, educational or other occurrences. In many cases information derived from an Online Social Network is acted upon and often shared with other networks, without further assessments or judgments. Many people do not check to see if the information shared is credible. A user may trust the information generated by a close friend without questioning its credibility, in contrast to a message generated by an unknown user. This work considers the concept of credibility in the wider sense, by proposing whether a user can trust the service provider or even the information itself. Two key components of credibility have been explored; trustworthiness and expertise. Credibility has been researched in the past using Twitter as a validation tool. The research was focused on automatic methods of assessing the credibility of sets of tweets using analysis of microblog postings related to trending topics to determine the credibility of tweets. This research develops a framework that can assist the assessment of the credibility of messages in Online Social Networks. Four types of credibility are explored (experienced, surface, reputed and presumed credibility) resulting in a credibility hierarchy. To determine the credibility of messages generated and distributed in Online Social Networks, a virtual network is created, which attributes nodes with individual views to generate messages in the network at random, recording data from a network and analysing the data based on the behaviour exhibited by agents (an agent-based modelling approach). The factors considered for the experiment design included; peer-to-peer networking, collaboration, opinion formation and network rewiring. The behaviour of agents, frequency in which messages are shared and used, the pathway of the messages and how this affects credibility of messages is also considered. A framework is designed and the resulting data are tested using the design. The resulting data generated validated the framework in part, supporting an approach whereby the concept of tagging the message status assists the understanding and application of the credibility hierarchy. Validation was carried out with Twitter data acquired through twitter’s Application Programming Interface (API). There were similarities in the generation and frequency of the message distributions in the network; these findings were also recorded and analysed using the framework proposed. Some limitations were encountered while acquiring data from Twitter, however, there was sufficient evidence of correlation between the simulated and real social network datasets to indicate the validity of the framework.

This study focuses on two roll-outs of a, year-long National Qualification Framework (NQF) level 5, environmental education learnership in South Africa and attempts at enhancing collaborative learning at workplaces using a familiar social networking site called Facebook. This study uses the Facebook group sites created for the workplace course component of the course as one of the means of data collection. Additional interviews and focus groups with learners and administrators on both Environmental Education Training and Development Practices (EETDP) courses also informed the study. The study is located within the context of the rise of the information age, its effects on socio-ecological landscape at large and ways of using social networking sites in order to facilitate scaffolding and meaning making within zones of proximal development for environmental education learnerships. It also looks at the model of apprenticeship and workplace based learning as it is broadly located at the nexus of the SAQA-led academic inquiry into workplace based learning and professional development. It was found that the use of Facebook on the EETDP learnership allowed for collaborative learning to take place between peer to peer interactions as well as between tutors and learners. It was also noted that scaffolding processes requires both technical assistance and strong instructional input from course tutors. One of the most important findings in terms of collaborative learning and engaging within the Zone of Proximal Development (ZPD) was that learners were able to communicate more effectively and freely with both fellow learners and tutors on course after participating on the Facebook group sites. The study offers recommendations on how a social networking platform like Facebook can be utilised effectively for environmental education. The study recommends that scaffolding of workplace based tasks and concepts needs to be better integrated with the course and in both online and offline interactions between learners. It also illustrates how social networking sites can become powerful tools for creating meaning making when combined with course work.

Made available in DSpace on 2016-06-02T19:05:54Z (GMT). No. of bitstreams: 1 4059.pdf: 2485259 bytes, checksum: 983984e4a04b36bece1e3d350804b5e9 (MD5) Previous issue date: 2011-08-25 / The use of online social networks for sharing personal data is becoming increasingly common. To join an online social network, users must agree to the online social networks policies and this generally implies agreeing that all posted data can be used for various purposes, for instance, to improve the service offered by the social network operator. Online social networks generally provide tools to allow users to restrict access to their shared data. However, these access restrictions applies only to social network users, enabling third parties and the social network itself access and use to these data. A data encryption based approach only is insufficient to ensure privacy and preserve the ability of the user to obtain personalized services. This paper presents a mechanism based on a well-known message format coupled with the use of methods for symmetric and asymmetric encryption to extend the privacy in online social networks, ensuring that certain user data types remain private to other network users, third parties and own social network, yet allowing the offering of personalized services. Additionally, a case study using the mechanism in a real online social network and an analysis of the mechanism are presented. / A utilização de redes sociais online para o compartilhamento de dados está se tornando cada vez mais comum. Para se inscrever em uma rede social online, os usuários devem concordar com as políticas que estas redes impõem e isto implica, na maioria das vezes, em concordar que todos os dados postados podem ser utilizados para diversos fins, por exemplo, para a melhoria do serviço oferecido pela rede social. Ao mesmo tempo, as redes sociais online geralmente fornecem ferramentas para que o acesso aos dados compartilhados pelos usuários seja restrito. No entanto, esta restrição de acesso aplicase apenas para usuários da rede social, possibilitando que terceiros e a própria rede social possam acessar e utilizar estes dados. Uma abordagem somente com criptografia dos dados é insuficiente para que a privacidade destes dados seja fornecida mantendo a possibilidade do usuário obter serviços personalizados. Este trabalho apresenta um mecanismo baseado em um formato de mensagens bem conhecido juntamente com a utilização de métodos de criptografia simétrica e assimétrica para estender a privacidade em redes sociais online, garantindo a privacidade de certos tipos de dados dos usuários em relação a outros usuários da rede, a terceiros e a própria rede social, possibilitando mesmo assim a aplicação de serviços personalizados para os usuários da rede social. Adicionalmente, um estudo de caso com a utilização do mecanismo em uma rede social online real e uma análise sobre o mecanismo são apresentados.