A Multi-View Sentiment Corpus

Debora Nozza, Elisabetta Fersini, Enza Messina


Abstract
Sentiment Analysis is a broad task that involves the analysis of various aspect of the natural language text. However, most of the approaches in the state of the art usually investigate independently each aspect, i.e. Subjectivity Classification, Sentiment Polarity Classification, Emotion Recognition, Irony Detection. In this paper we present a Multi-View Sentiment Corpus (MVSC), which comprises 3000 English microblog posts related the movie domain. Three independent annotators manually labelled MVSC, following a broad annotation schema about different aspects that can be grasped from natural language text coming from social networks. The contribution is therefore a corpus that comprises five different views for each message, i.e. subjective/objective, sentiment polarity, implicit/explicit, irony, emotion. In order to allow a more detailed investigation on the human labelling behaviour, we provide the annotations of each human annotator involved.
Anthology ID:
E17-1026
Volume:
Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers
Month:
April
Year:
2017
Address:
Valencia, Spain
Venue:
EACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
273–280
Language:
URL:
https://aclanthology.org/E17-1026
DOI:
Bibkey:
Cite (ACL):
Debora Nozza, Elisabetta Fersini, and Enza Messina. 2017. A Multi-View Sentiment Corpus. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers, pages 273–280, Valencia, Spain. Association for Computational Linguistics.
Cite (Informal):
A Multi-View Sentiment Corpus (Nozza et al., EACL 2017)
Copy Citation:
PDF:
https://aclanthology.org/E17-1026.pdf