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.

Developing Corpora for Sentiment Analysis: The Case of Irony and Senti-TUT (Extended Abstract)

BOSCO, CRISTINA;PATTI, Viviana;
2015-01-01

Abstract

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.
2015
International Joint Conference on Artificial Intelligence, IJCAI 2015
Buenos Aires, Argentina
July 25-31
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI 2015
AAAI Press
4158
4162
978-1-57735-738-4
http://www.aaai.org/ocs/index.php/IJCAI/IJCAI15/paper/view/10921
https://www.ijcai.org/Proceedings/15/Papers/587.pdf
https://www.ijcai.org/Abstract/15/587
Sentiment Analysis, Ironia, Twitter
Bosco, Cristina; Patti, Viviana; Bolioli, Andrea
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1535815
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