Entity extraction e text classification come strumenti per la sentiment analysis di testi giornalistici

In this thesis we are going to talk about technologies which allow us to approach sentiment analysis on newspapers articles. The final goal of this work is to help social scholars to do content analysis on big corpora of texts in a faster way thanks to the support of automatic text classification.

In Your Face! Investigating Facework, Criticism, and Humour with Corpora in Electoral Debates

In political debates, the media[tisation] can determine the use of language with the aim to increase their spectacularisation and polarisation, possibly by means of criticism and humour, respectively. These linguistic strategies are often used in order to shape what was defined by Goffman as one’s face. Politicians, in particular, can recur to facework in a double sense: shaping their own face positively and/or that of their opponents negatively. Starting from the sociologic theory of face by Goffman and Levinson, with the help of corpus analysis tools, this research investigated the ways in which various forms of criticism and forms of humour were conducted in 3 electoral debates on a national scale (Germany, Ireland, and New Zealand) and 1 debate for the municipal election in Rome. The transcripts were revised after automatic transcriptions were extracted or found online, of which the audio-visual content is available on the Internet. The CADS research aimed to investigate the role that criticism and humour played within each participant’s discourse, and to identify differences and similarities among the strategies used by political leaders and moderators in different countries, and in different cultural, political, and media contexts.