In machine learning, a fundamental challenge is the analysis of data to identify feelings using algorithms that allow us to determine the positive or negative emotions that people have regarding a topic. Social networks and microblogging are a valuable source of information, being mostly used to express personal points of view and thoughts. Based on this knowledge we propose a sentiment analysis of English tweets during the pandemic COVID-19 in 2020. The tweets were classified as positive or negative by applying the Logistic Regression algorithm, using this method we got a classification accuracy of 78.5%.

To achieve the most understandable and accurate display of information, a study on the available techniques of data visualization for real-time information must be made. Customizing existing platforms and designing specific boards, are among the important task to perform an accurate visualization of the information. In this paper, we conduct a literature review of data visualization, its techniques and existing dashboard platforms. We implemented a generic and dynamic dashboard based on real-time information with the aim to assess the impact of the available Data Visualization Techniques in the developed dashboard. Therefore, our Dashboard users will be able to interact with the information, based on an initial set of hints, charts, tables and reports, produced by the Dashboard itself. This will allow us to test an existing set of data visualization techniques and create a new tailored dashboard, showing that dashboards can become a unique and powerful means to provide information.

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