ComentCorpus: identificação e pistas linguísticas para detecção de ironia no português do Brasil
Pedro, Gabriela Wick
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Opinions on the Web have been increasing progressively and, thus, has aroused interest in areas of study of Linguistics and Computation, for example. In this context comes the Sentiment Analysis, or Opinion Mining, which aims to analyze computationally opinions, emotions, feelings and subjectivities present in texts (LIU, 2012), however, certain subjective sentences can carry irony, transforming the meaning of a sentence. This dissertation aims to investigate expressions of irony in social media, focusing on the description of linguistic devices as clues of irony in opinion texts in Brazilian Portuguese. To understand the functioning of this figurative mechanism, we will start from the search a corpus constructed by new commentaries from the Folha de S. Paulo portal. In addiction, based on pragmatic and cognitive theories, we developed a corpus annotation scheme for opinions and their intentions: ironic, other types of irony or non-ironic. As a result, we have obtained a list of subcategories that characterize expressions of irony that allow to collaborate with the development of the NLP area and Sentiment Analysis and, in addition, to improve tools of automatic identification of opinion through the descriptions and the linguistic resources elaborated here.