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Political debate - in its essence - carries a robust emotional charge, and social media have become a vast arena for voters to disseminate and discuss the ideas proposed by candidates. The Brazilian presidential elections of 2018 were marked by a high level of polarization, making the discussion of the candidates’ ideas an ideological battlefield, full of accusations and verbal aggression, creating an excellent source for sentiment analysis. In this paper, we analyze the emotions of the tweets posted about the presidential candidates of Brazil on Twitter, so that it was possible to identify the emotional profile of the adherents of each of the leading candidates, and thus to discern which emotions had the strongest effects upon the election results. Also, we created a model using sentiment analysis and machine learning, which predicted with a correlation of 0.90 the final result of the election., FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2019

This paper presents two simple experiments performed in order to enlarge the coverage of PULO, a Lexical Ontology, based and aligned with the Princeton WordNet. The first experiment explores the triangulation of the Galician, Catalan and Castillian wordnets, with translation dictionaries from the Apertium project. The second, explores Dicionário-Aberto entries, in order to extract synsets from its definitions. Although similar approaches were already applied for different languages, this document aims at documenting their results for the PULO case.

This paper details the SysBio Explorer, a Systems Biology Literature Retrieval and Processing Framework, whose aim relies on the automatic inference of regulatory and metabolic networks based on biomedical literature. The SysBio Explorer does not focus on any organism or problem in particular and encompasses a number of processing and analysis techniques. It works over full-text documents, applying Natural Language Processing techniques and using biomedical dictionaries and ontologies together with hand-made rules. Besides biological entity recognition and relation extraction, document classification, relevance assessment and authoring networks are also within its present scope. The framework is described in terms of its design requirements and implementation decisions, exposing current achievements, but also highlighting present obstacles and future work. Experiments over realworld problems concerning the organisms E. coli, S. cerevisiae and H. pylori are used in its validation., Fundação para a Ciência e a Tecnologia (FCT) - POCI/BIO/60139/2004; POSI/PLP/43931/2001; POSC project POSC/339/1.3/C/NAC., Fundação para a Computação Científica Nacional.