@inproceedings{de-bruyne-etal-2020-emotional,
title = "An Emotional Mess! Deciding on a Framework for Building a {D}utch Emotion-Annotated Corpus",
author = "De Bruyne, Luna and
De Clercq, Orphee and
Hoste, Veronique",
booktitle = "Proceedings of the Twelfth Language Resources and Evaluation Conference",
month = may,
year = "2020",
address = "Marseille, France",
publisher = "European Language Resources Association",
url = "https://aclanthology.org/2020.lrec-1.204",
pages = "1643--1651",
abstract = "Seeing the myriad of existing emotion models, with the categorical versus dimensional opposition the most important dividing line, building an emotion-annotated corpus requires some well thought-out strategies concerning framework choice. In our work on automatic emotion detection in Dutch texts, we investigate this problem by means of two case studies. We find that the labels joy, love, anger, sadness and fear are well-suited to annotate texts coming from various domains and topics, but that the connotation of the labels strongly depends on the origin of the texts. Moreover, it seems that information is lost when an emotional state is forcedly classified in a limited set of categories, indicating that a bi-representational format is desirable when creating an emotion corpus.",
language = "English",
ISBN = "979-10-95546-34-4",
}
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<abstract>Seeing the myriad of existing emotion models, with the categorical versus dimensional opposition the most important dividing line, building an emotion-annotated corpus requires some well thought-out strategies concerning framework choice. In our work on automatic emotion detection in Dutch texts, we investigate this problem by means of two case studies. We find that the labels joy, love, anger, sadness and fear are well-suited to annotate texts coming from various domains and topics, but that the connotation of the labels strongly depends on the origin of the texts. Moreover, it seems that information is lost when an emotional state is forcedly classified in a limited set of categories, indicating that a bi-representational format is desirable when creating an emotion corpus.</abstract>
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%0 Conference Proceedings
%T An Emotional Mess! Deciding on a Framework for Building a Dutch Emotion-Annotated Corpus
%A De Bruyne, Luna
%A De Clercq, Orphee
%A Hoste, Veronique
%S Proceedings of the Twelfth Language Resources and Evaluation Conference
%D 2020
%8 May
%I European Language Resources Association
%C Marseille, France
%@ 979-10-95546-34-4
%G English
%F de-bruyne-etal-2020-emotional
%X Seeing the myriad of existing emotion models, with the categorical versus dimensional opposition the most important dividing line, building an emotion-annotated corpus requires some well thought-out strategies concerning framework choice. In our work on automatic emotion detection in Dutch texts, we investigate this problem by means of two case studies. We find that the labels joy, love, anger, sadness and fear are well-suited to annotate texts coming from various domains and topics, but that the connotation of the labels strongly depends on the origin of the texts. Moreover, it seems that information is lost when an emotional state is forcedly classified in a limited set of categories, indicating that a bi-representational format is desirable when creating an emotion corpus.
%U https://aclanthology.org/2020.lrec-1.204
%P 1643-1651
Markdown (Informal)
[An Emotional Mess! Deciding on a Framework for Building a Dutch Emotion-Annotated Corpus](https://aclanthology.org/2020.lrec-1.204) (De Bruyne et al., LREC 2020)
ACL