@inproceedings{stajner-klinger-2023-emotion,
title = "Emotion Analysis from Texts",
author = "Stajner, Sanja and
Klinger, Roman",
editor = "Zanzotto, Fabio Massimo and
Pradhan, Sameer",
booktitle = "Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics: Tutorial Abstracts",
month = may,
year = "2023",
address = "Dubrovnik, Croatia",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.eacl-tutorials.2",
doi = "10.18653/v1/2023.eacl-tutorials.2",
pages = "7--12",
abstract = "Emotion analysis in text is an area of research that encompasses a set of various natural language processing (NLP) tasks, including classification and regression settings, as well as structured prediction tasks like role labelling or stimulus detection. In this tutorial, we provide an overview of research from emotion psychology which sets the ground for choosing adequate NLP methodology, and present existing resources and classification methods used for emotion analysis in texts. We further discuss appraisal theories and how events can be interpreted regarding their presumably caused emotion and briefly introduce emotion role labelling. In addition to these technical topics, we discuss the use cases of emotion analysis in text, their societal impact, ethical considerations, as well as the main challenges in the field.",
}
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%0 Conference Proceedings
%T Emotion Analysis from Texts
%A Stajner, Sanja
%A Klinger, Roman
%Y Zanzotto, Fabio Massimo
%Y Pradhan, Sameer
%S Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics: Tutorial Abstracts
%D 2023
%8 May
%I Association for Computational Linguistics
%C Dubrovnik, Croatia
%F stajner-klinger-2023-emotion
%X Emotion analysis in text is an area of research that encompasses a set of various natural language processing (NLP) tasks, including classification and regression settings, as well as structured prediction tasks like role labelling or stimulus detection. In this tutorial, we provide an overview of research from emotion psychology which sets the ground for choosing adequate NLP methodology, and present existing resources and classification methods used for emotion analysis in texts. We further discuss appraisal theories and how events can be interpreted regarding their presumably caused emotion and briefly introduce emotion role labelling. In addition to these technical topics, we discuss the use cases of emotion analysis in text, their societal impact, ethical considerations, as well as the main challenges in the field.
%R 10.18653/v1/2023.eacl-tutorials.2
%U https://aclanthology.org/2023.eacl-tutorials.2
%U https://doi.org/10.18653/v1/2023.eacl-tutorials.2
%P 7-12
Markdown (Informal)
[Emotion Analysis from Texts](https://aclanthology.org/2023.eacl-tutorials.2) (Stajner & Klinger, EACL 2023)
ACL
- Sanja Stajner and Roman Klinger. 2023. Emotion Analysis from Texts. In Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics: Tutorial Abstracts, pages 7–12, Dubrovnik, Croatia. Association for Computational Linguistics.