Moral Stance Recognition and Polarity Classification from Twitter and Elicited Text

Wesley Santos, Ivandré Paraboni


Abstract
We introduce a labelled corpus of stances about moral issues for the Brazilian Portuguese language, and present reference results for both the stance recognition and polarity classification tasks. The corpus is built from Twitter and further expanded with data elicited through crowd sourcing and labelled by their own authors. Put together, the corpus and reference results are expected to be taken as a baseline for further studies in the field of stance recognition and polarity classification from text.
Anthology ID:
R19-1123
Volume:
Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019)
Month:
September
Year:
2019
Address:
Varna, Bulgaria
Editors:
Ruslan Mitkov, Galia Angelova
Venue:
RANLP
SIG:
Publisher:
INCOMA Ltd.
Note:
Pages:
1069–1075
Language:
URL:
https://aclanthology.org/R19-1123
DOI:
10.26615/978-954-452-056-4_123
Bibkey:
Cite (ACL):
Wesley Santos and Ivandré Paraboni. 2019. Moral Stance Recognition and Polarity Classification from Twitter and Elicited Text. In Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019), pages 1069–1075, Varna, Bulgaria. INCOMA Ltd..
Cite (Informal):
Moral Stance Recognition and Polarity Classification from Twitter and Elicited Text (Santos & Paraboni, RANLP 2019)
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PDF:
https://preview.aclanthology.org/emnlp22-frontmatter/R19-1123.pdf