A New Machine Learning Based Approach for Sentiment Classification of Italian documents

Several sites allow users to publish personal reviews about products and services available on the market. In this paper, we consider the problem of applying classification techniques to identify, in terms of positive or negative degree, the overall opinion polarity expressed in these documents, written in natural language. In particular, we are interested in evaluating the performance obtained by applying machine learning techniques, based on n-gram selection and originally developed for English, to documents written in Italian. In order to obtain results comparable to those presented in the literature for English, we use the same evaluation procedure applied in the majority of the works in this field. We have developed a specific framework for experimentation in Italian. The research is ongoing and we present some preliminary results, a comparison with results presented in literature and an overview of our future work.

• Type: Conference
• Year: 2008
• Where: IRCDL
• Authors: Paolo Casoto, Antonina Dattolo, Paolo Omero, Nirmala Pudota, Carlo Tasso
• Keywords: Digital Library, IRCDL 2008, Machine Learning Techniques, Overall Opinion Polarity, Sites Allow Users