The LiLaH Emotion Lexicon of Croatian, Dutch and Slovene

Nikola Ljubešić, Ilia Markov, Darja Fišer, Walter Daelemans


Abstract
In this paper, we present emotion lexicons of Croatian, Dutch and Slovene, based on manually corrected automatic translations of the English NRC Emotion lexicon. We evaluate the impact of the translation changes by measuring the change in supervised classification results of socially unacceptable utterances when lexicon information is used for feature construction. We further showcase the usage of the lexicons by calculating the difference in emotion distributions in texts containing and not containing socially unacceptable discourse, comparing them across four languages (English, Croatian, Dutch, Slovene) and two topics (migrants and LGBT). We show significant and consistent improvements in automatic classification across all languages and topics, as well as consistent (and expected) emotion distributions across all languages and topics, proving for the manually corrected lexicons to be a useful addition to the severely lacking area of emotion lexicons, the crucial resource for emotive analysis of text.
Anthology ID:
2020.peoples-1.15
Volume:
Proceedings of the Third Workshop on Computational Modeling of People's Opinions, Personality, and Emotion's in Social Media
Month:
December
Year:
2020
Address:
Barcelona, Spain (Online)
Editors:
Malvina Nissim, Viviana Patti, Barbara Plank, Esin Durmus
Venue:
PEOPLES
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
153–157
Language:
URL:
https://aclanthology.org/2020.peoples-1.15
DOI:
Bibkey:
Cite (ACL):
Nikola Ljubešić, Ilia Markov, Darja Fišer, and Walter Daelemans. 2020. The LiLaH Emotion Lexicon of Croatian, Dutch and Slovene. In Proceedings of the Third Workshop on Computational Modeling of People's Opinions, Personality, and Emotion's in Social Media, pages 153–157, Barcelona, Spain (Online). Association for Computational Linguistics.
Cite (Informal):
The LiLaH Emotion Lexicon of Croatian, Dutch and Slovene (Ljubešić et al., PEOPLES 2020)
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PDF:
https://aclanthology.org/2020.peoples-1.15.pdf