An Italian Corpus for Aspect Based Sentiment Analysis of Movie Reviews
Authors: Antonio Sorgente, Giuseppe Vettigli, Francesco Mele (CNR-ICIB, 2014)
Topic: Sentiment, Emotion, Irony, Hate

Abstract
In this paper we will present an Italian corpus focused on the domain of movie reviews, developed in order to sup-port our ongoing research for the devel-opment of new models about Sentiment Analysis and Aspect Identification in Ital-ian language. The corpus that we will present contains a set of sentences man-ually annotated according to the various aspects of the movie that have been dis-cussed in the sentence and the polarity expressed towards that particular aspect. In this paper we will present the anno-tation guidelines applied, some statistics about the corpus and the preliminary re-sults about the identification of the aspects.

Introduction
Nowadays, on the Web there is a huge amount of unstructured information about public opinion and it continues growing up rapidly. Analysing the opinions expressed by the users is an important step to evaluate the quality of a product. In this scenario, the tools provided by Sentiment Analy-sis and Opinion Mining are crucial to process this information. In the particular case of movie re-views, we have that the number of reviews that a movie receives on-line grows quickly. Some pop-ular movies can receive hundreds of reviews and, furthermore, many reviews are long and some-times they contain only few sentences expressing the actual opinions. This makes hard for a poten-tial viewer to read them and make an informed decision about whether to watch a movie or not. In the case that one only reads a few reviews, the choice may be biased. The large number of reviews also makes it hard for movie producers to keep track of viewer’s opinions. The recent advances in Sentiment Analysis have shown that coarse overall sentiment scores fails to adequately represent the multiple potential aspects on which an entity can be evaluated (Socher et al., 2013). For example, if we consider the following review from Amazon.com about the movie Inception: “By far one of the best movies I’ve ever seen. Visually stunning and mentally challenging. I would recommend this movie to people who are very deep and can stick with a movie to get the true meaning of the story.” One can see that, even if the review is short, it not only expresses an overall opinion but also contains opinions about other two aspects of the movie: the photography and the story. So, in order to obtain a more detailed sentiment, an analysis that considers different aspects is required. In this work, we present an Italian corpus fo-cused on the domain of movie reviews developed in order to support our ongoing effort for the de-velopment of new models about Sentiment Analy-sis and Aspect Identification in Italian language. The paper is structured as follows. In the Sec-tion 2 we present the motivations that led us to the creation of a new corpus and a short survey about related resources that already exist. Section 3 de-scribes the guideline used to annotate the corpora, while Section 4 presents some statistical informa-tion about it. In section 5 we present some prelimi-nary experiments about the identification of the as-pects. Finally, in section 6 some conclusions will be offered.

Conclusion
We introduced an Italian corpus of sentences ex-tracted by movie reviews. The corpus has been specifically designed to support the development of new tools for the Sentiment Analysis in Italian. We believe that corpus can be used to train and test new models for sentence-level sentiment clas-sification and aspect-level opinion extractions. In the paper, various aspects of the corpus we created have been described. Also, the results of some preliminary experiments about the automatic identification of the aspects have been showed.