Lucia C. Passaro

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In this paper we compare different context selection approaches to improve the creation of Emotive Vector Space Models (VSMs). The system is based on the results of an existing approach that showed the possibility to create and update VSMs by exploiting crowdsourcing and human annotation. Here, we introduce a method to manipulate the contexts of the VSMs(More)
English. In this paper we present the FBNEWS15 corpus, a new Italian resource for sentiment analysis and emotion detection. The corpus has been built by crawling the Facebook pages of the most important newspapers in Italy and it has been organized into topics using LDA. In this work we provide a preliminary analysis of the corpus, including the most(More)
English. This paper describes the CoLing Lab system for the participation in the constrained run of the EVALITA 2016 SENTIment POLarity Classification Task (Barbieri et al., 2016). The system extends the approach in (Passaro et al., 2014) with emotive features extracted from ItEM (Passaro et al., 2015; Passaro and Lenci, 2016) and FB-NEWS15 (Passaro et al.,(More)
PURPOSE To study the relation between the average level and variability of blood pressure (VBP) obtained by ambulatory monitoring (AMBP) and the geometric pattern (GP) of the left ventricle (LV) obtained by echocardiography (ECHO) in patients with hypertension (Hy) METHODS AMBP and ECHO were performed in 37 patients with Hy, divided into three groups:(More)
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