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The huge increase in online content has rapidly stepped up the challenges facing various entities such as organisations, businesses, governments. Dealing with this immense increase in information is beyond any human ability, as it requires massive efforts to go through huge volumes of posts/news to analyse and understand their content. In responding to this challenge, research has picked up in recent years to automatically analyse, and extract opinions/sentiment from online content. This thesis investigated the area of sentiment analysis and its impact on financial market entities. The thesis includes a review of the sentiment analysis processes, an overview of sentiment analysis studies and their application to the financial markets domain. The literature shows a gap in defining systematic and reusable evaluation processes, for users to automatically conduct impact analysis of sentiment datasets in different financial contexts. In addressing the research gap the thesis proposes a framework called News Sentiment Impact Analysis (NSIA) which consists of three components which are a conceptual data model, a software architecture, and a set of use cases. The key component which is the conceptual data model captures three sets of parameters: the financial context parameters, the sentiment related parameters, and the impact measure parameters. The CPD model is supported by a software architecture, which consists of a GUI, Business, and Data layers. The main use case allows the analyst to define the CPD parameters using the provided GUI layer and trigger the impact analysis process. To evaluate the proposed framework, a prototype is implemented. Three case studies have been conducted to evaluate the different aspects of the proposed framework. The case studies results show that the proposed NSIA framework meets the research objectives and demonstrate the flexibility of the proposed NSIA framework for conducting impact analysis in various contexts, using different sentiment extractions techniques, and various impact ...

Numa era de migrações, muitos dos países desenvolvidos enfrentam uma crescente heterogeneidade populacional. Os fluxos migratórios têm levado muitas vezes a uma discussão política sobre o impacto dos imigrantes nos mercados laborais, no crescimento económico e nos processos de aglomeração urbana. Consequentemente muitos destes efeitos são uma fonte de debate nos círculos políticos e na investigação académica. Neste artigo que analisa o impacto da migração temos uma abordagem abrangente, embora não exaustiva, à investigação sobre efeitos das migrações e desenvolvimento económico. O impacto dos migrantes no crescimento e desenvolvimento económico depende em grande parte do âmbito e da escala da investigação , tal como a geografia do mercado laboral e a heterogeneidade dos migrantes. No geral, não foi encontrado um impacto claramente negativo da migração na economia, num nível agregado, a longo prazo. No entanto, no curto prazo, acontecem alguns ajustamentos ao nível regional. Mas é necessário mais pesquisa e mais dados para descobrir qual é exactamente a relação entre migração e crescimento económico.

Significant progress has been made in recent years in the field of image processing, particularly in facial recognition. The number of deployments and experiments of this type of system is rapidly increasing. Most applications are motivated either by security or by commercial considerations. However, there are different opinions regarding the use of these systems, particularly in the public space. Considering the lack of consensus on a technology that can have a significant impact on society, many organizations have alerted public opinion and called for a public debate on this topic. We believe that such a debate is indeed necessary. However, for such a debate to be productive, it is essential to ensure that arguments can be expressed and confronted in a rigorous way. In particular, it is critical to avoid, as much as possible, preconceptions and to distinguish established facts from assumptions or opinions. The purpose of this document is precisely to set the terms of the debate on a solid basis. Our aim is not to take a position on facial recognition in general or to provide an exhaustive review of its applications, but rather to propose some elements of methodology for the analysis of its impacts, illustrated by some examples. The importance of conducting impact assessments of facial recognition technologies is underlined by institutions such as the European Commission and the European Union Agency for Fundamental Rights (FRA) but there is still a lack of methodology to put them into practice. As facial recognition applications are very different, it is necessary to precisely analyse the potential impacts of each system, taking into account all its features and the context of its deployment. However, this case-by-case analysis should not overlook the more "systemic" risk related to a potential generalization of the reliance on facial recognition in our societies. This global risk must also be analysed and debated because it may justify, according to some people, a total or partial ban of facial recognition.