Similaridade entre perfis sociais

Mestrado em Sistemas de InformaçãoNa última década, a utilização da Internet tornou-se viral e de extrema importância posicionando-se, atualmente, numa parte integral das nossas vidas incluindo a parte social. As redes sociais online são uma das fontes mais ricas de informação sobre os perfis de utilizadores. Ao lidar com dados de redes sociais, a similaridade entre perfis representa uma área que tem tido algum destaque. Uma ferramenta capaz de identificar corretamente utilizadores semelhantes pode ser utilizada em diversas áreas e contribuir para tomadas de decisão importantes que poderão resultar em proveitos, sejam de cariz financeiro ou melhoria da qualidade de vida de pessoas (por exemplo, saúde). Nesta dissertação são realizados estudos com diferentes métricas de distância de forma a determinar a similaridade entre perfis. É possível, também, criar agrupamentos de perfis assim como correlacionar interesses. Posteriormente, é feita uma análise de performance entre diversos algoritmos de clustering, nomeadamente o K-Means, Clustering Hierárquico, DBSCAN e BIRCH. As medidas de similaridade foram também utilizadas para estimar valores associados aos interesses dos utilizadores, numa abordagem inspirada nos sistemas de recomendação.Over the last decade, Internet usage has gone viral and become extremely important, positioning itself as an integral part of our lives and social interactions. Social networks are now one of the richest sources of information regarding user profiles. By dealing with social network data, an area that as recently seen growing interest, one can create methods to study profile similarity, using available user data. A possible tool to correctly identify similar users may be applied in a multitude of areas and contribute to the decision making process that may draw gains to people’s lives, either in financial perspective or life quality (such as health). In this dissertation, metrics that are applied when determining profile similarity were researched and discussed, giving a complete overview on the concepts involved and difficulties experienced. Moreover, it is possible to create profile clusters as well as correlate interests. As such, a performance analysis of different clustering algorithms is done, namely K-Means, Hieratical Clustering, DBSCAN and BIRCH. Techniques used in recommendations systems are also discussed. Finally, future work is proposed where this project would serve as the basis of a recommendation and profile analysis systems

Adding, Retrieving and Browsing Content in Social Media and E-Journalism

This thesis explores the use of avatars with facial expressions in social media and e-journalism communication interfaces. This thesis involved three experimental conditions. In the first experimental condition a survey (n=34) and an experiment (n=25) were carried out in order to explore the central problems faced by users during adding and retrieving comments and methods to overcome those problems. The survey intended to find out the position users took towards these metaphors. 25users from the Aljazeera Channel in Doha, Qatar took part. The first experimental condition consisted of two interfaces, TARCS (traditional adding and retrieving comments system) and CMARCS (classification multimodal adding and retrieving comments system). This was carried out in order to assess users' perception of unique text with graphic classification and multimodal in an EARCS (electronic adding and retrieving comments system) interface in the presence and absence of an interactive context. This was implemented in order to assess the role of these unique classification interfaces in a news comment in the term of usability. In the second experiment, forty users evaluated the use of the VARCS (visual adding and retrieving comments system) and MMARCS (multimodal adding and retrieving comments system). Both interfaces evaluated the effect on public opinion as media study and effectiveness, interactivity and user satisfaction in HCI studies. The third experimental condition consisted of one study that investigated the impactbility and usability of facial expressions compared text with graphic and multimodal metaphors. Sixty six users from Al-Arabiya Channel in Dubai, UEA took part in these two experiments. The results obtained show that users had some problems with adding and retrieving comments in social media such as missing data and lack of organisation. Also, the new classification performed better and faster under an interface that implemented avatars with specific facial expressions compared to a textual interface and multimodal. Practical guidelines were also introduced to provide assistance to multimedia designers who use avatars with facial expressions in e-journalism interactive systems as well as its impact on the public opinion.Ministry of High Education in Saudi, the Saudi Arabian Cultural Bureau, Al-Jazeera Channel, MBC Group and Al-Arabiya Channe

Radio Communications

In the last decades the restless evolution of information and communication technologies (ICT) brought to a deep transformation of our habits. The growth of the Internet and the advances in hardware and software implementations modified our way to communicate and to share information. In this book, an overview of the major issues faced today by researchers in the field of radio communications is given through 35 high quality chapters written by specialists working in universities and research centers all over the world. Various aspects will be deeply discussed: channel modeling, beamforming, multiple antennas, cooperative networks, opportunistic scheduling, advanced admission control, handover management, systems performance assessment, routing issues in mobility conditions, localization, web security. Advanced techniques for the radio resource management will be discussed both in single and multiple radio technologies; either in infrastructure, mesh or ad hoc networks