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Quantifying implicit political intentions in parliamentary discourse - an integrated approach using semi-supervised learning and vector space information retrieval
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Resumo(s)
Recent advances in Natural Language Processing and Information Retrieval have opened a new world of possibilities for the analysis of text. This study seeks to explore the possibilities of applying these techniques on political text, with a focus on quantifying intentions in parliamentary speeches and activities in Portugal. Combining vector space models and semi-supervised learning, a semantic search engine is able to extract meaningful metrics from text that help to identify political trends and quantify alignment with political issues.
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Palavras-chave
Natural language processing Political science Semi-supervised learning Informational retrieval Discourse analysis Business analysis