S. Stajner, and R. Klinger. Proceedings of the 17th Conference of the European
Chapter of the Association for Computational
Linguistics: Tutorial Abstracts, Dubrovnik, Croatia, Association for Computational Linguistics, (May 2023)
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 labeling 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
labeling. 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.
%0 Conference Paper
%1 StajnerKlinger2023
%A Stajner, Sanja
%A Klinger, Roman
%B Proceedings of the 17th Conference of the European
Chapter of the Association for Computational
Linguistics: Tutorial Abstracts
%C Dubrovnik, Croatia
%D 2023
%I Association for Computational Linguistics
%K emotion imported language myown nlp tutorial
%T Emotion Analysis in Text
%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 labeling 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
labeling. 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.
@inproceedings{StajnerKlinger2023,
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 labeling 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
labeling. 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.},
added-at = {2023-04-06T10:18:01.000+0200},
address = {Dubrovnik, Croatia},
author = {Stajner, Sanja and Klinger, Roman},
biburl = {https://puma.ub.uni-stuttgart.de/bibtex/25c92fa34ba6673bee8754e893af401c3/dr.romanklinger},
booktitle = {Proceedings of the 17th Conference of the European
Chapter of the Association for Computational
Linguistics: Tutorial Abstracts},
interhash = {99ccde666081dc00304d13d449e9240a},
internaltype = {confabstracts},
intrahash = {5c92fa34ba6673bee8754e893af401c3},
keywords = {emotion imported language myown nlp tutorial},
month = May,
publisher = {Association for Computational Linguistics},
timestamp = {2023-04-06T10:18:01.000+0200},
title = {Emotion Analysis in Text},
year = 2023
}