@inproceedings{feldkamp-etal-2024-comparing,
title = "Comparing Tools for Sentiment Analysis of {D}anish Literature from Hymns to Fairy Tales: Low-Resource Language and Domain Challenges",
author = "Feldkamp, Pascale and
Kostkan, Jan and
Overgaard, Ea and
Jacobsen, Mia and
Bizzoni, Yuri",
editor = "De Clercq, Orph{\'e}e and
Barriere, Valentin and
Barnes, Jeremy and
Klinger, Roman and
Sedoc, Jo{\~a}o and
Tafreshi, Shabnam",
booktitle = "Proceedings of the 14th Workshop on Computational Approaches to Subjectivity, Sentiment, {\&} Social Media Analysis",
month = aug,
year = "2024",
address = "Bangkok, Thailand",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.wassa-1.15",
pages = "186--199",
abstract = "While Sentiment Analysis has become increasingly central in computational approaches to literary texts, the literary domain still poses important challenges for the detection of textual sentiment due to its highly complex use of language and devices - from subtle humor to poetic imagery. Furthermore these challenges are only further amplified in low-resource language and domain settings. In this paper we investigate the application and efficacy of different Sentiment Analysis tools on Danish literary texts, using historical fairy tales and religious hymns as our datasets. The scarcity of linguistic resources for Danish and the historical context of the data further compounds the challenges for the tools. We compare human annotations to the continuous valence scores of both transformer- and dictionary-based Sentiment Analysis methods to assess their performance, seeking to understand how distinct methods handle the language of Danish prose and poetry.",
}
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%0 Conference Proceedings
%T Comparing Tools for Sentiment Analysis of Danish Literature from Hymns to Fairy Tales: Low-Resource Language and Domain Challenges
%A Feldkamp, Pascale
%A Kostkan, Jan
%A Overgaard, Ea
%A Jacobsen, Mia
%A Bizzoni, Yuri
%Y De Clercq, Orphée
%Y Barriere, Valentin
%Y Barnes, Jeremy
%Y Klinger, Roman
%Y Sedoc, João
%Y Tafreshi, Shabnam
%S Proceedings of the 14th Workshop on Computational Approaches to Subjectivity, Sentiment, & Social Media Analysis
%D 2024
%8 August
%I Association for Computational Linguistics
%C Bangkok, Thailand
%F feldkamp-etal-2024-comparing
%X While Sentiment Analysis has become increasingly central in computational approaches to literary texts, the literary domain still poses important challenges for the detection of textual sentiment due to its highly complex use of language and devices - from subtle humor to poetic imagery. Furthermore these challenges are only further amplified in low-resource language and domain settings. In this paper we investigate the application and efficacy of different Sentiment Analysis tools on Danish literary texts, using historical fairy tales and religious hymns as our datasets. The scarcity of linguistic resources for Danish and the historical context of the data further compounds the challenges for the tools. We compare human annotations to the continuous valence scores of both transformer- and dictionary-based Sentiment Analysis methods to assess their performance, seeking to understand how distinct methods handle the language of Danish prose and poetry.
%U https://aclanthology.org/2024.wassa-1.15
%P 186-199
Markdown (Informal)
[Comparing Tools for Sentiment Analysis of Danish Literature from Hymns to Fairy Tales: Low-Resource Language and Domain Challenges](https://aclanthology.org/2024.wassa-1.15) (Feldkamp et al., WASSA-WS 2024)
ACL