Proceedings Abstracts of the Twenty-Fourth International Joint Conference on Artificial Intelligence

Developing Corpora for Sentiment Analysis: The Case of Irony and Senti-TUT (Extended Abstract) / 4188
Cristina Bosco, Viviana Patti, Andrea Bolioli

This paper focusses on the main issues related to the development of a corpus for opinion and sentiment analysis, with a special attention to irony, and presents as a case study Senti-TUT, a project for Italian aimed at investigating sentiment and irony in social media. We present the Senti-TUT corpus, a collection of texts from Twitter annotated with sentiment polarity. We describe the dataset, the annotation, the methodologies applied and our investigations on two important features of irony: polarity reversing and emotion expressions.