@inproceedings{storset-etal-2026-pain,
title = "From Pain to Praise: Aspect-Based Sentiment Analysis for {N}orwegian Patient Feedback",
author = "Storset, Lilja Charlotte and
Jelin, Elma and
Norman, Rebecka Maria and
Bjertnaes, Oyvind and
{\O}vrelid, Lilja and
Velldal, Erik",
editor = {Danilova, Vera and
Kurfal{\i}, Murathan and
S{\"o}derfeldt, Ylva and
Reed, Julia and
Burchell, Andrew},
booktitle = "Proceedings of the 1st Workshop on Linguistic Analysis for Health ({H}ea{L}ing 2026)",
month = mar,
year = "2026",
address = "Rabat, Morocco",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.healing-1.16/",
pages = "191--202",
ISBN = "979-8-89176-367-8",
abstract = "This paper describes a new dataset for aspect-based sentiment analysis (ABSA) for analyzing patient feedback about healthcare services. In an interdisciplinary collaboration spanning the fields of natural language processing and healthcare research, we manually annotate a dataset of 2382 free-text comments collected from national patient experience surveys in Norway, covering two sub-fields of services {--} special mental healthcare and general practitioners. Annotations are provided on both the sentence- and comment-level, covering a fine-grained set of 25 unique healthcare-related aspects and their polarities. We also report results for fine-tuning both encoder- and decoder models on the resulting dataset, comparing different modeling strategies, like joint and sequential prediction of aspects and polarity. The resources developed in this work can assist healthcare researchers in the analysis of patient feedback, bringing a much more efficient approach compared to today{'}s manual analysis, potentially leading to improved patient satisfaction and clinical outcomes."
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%0 Conference Proceedings
%T From Pain to Praise: Aspect-Based Sentiment Analysis for Norwegian Patient Feedback
%A Storset, Lilja Charlotte
%A Jelin, Elma
%A Norman, Rebecka Maria
%A Bjertnaes, Oyvind
%A Øvrelid, Lilja
%A Velldal, Erik
%Y Danilova, Vera
%Y Kurfalı, Murathan
%Y Söderfeldt, Ylva
%Y Reed, Julia
%Y Burchell, Andrew
%S Proceedings of the 1st Workshop on Linguistic Analysis for Health (HeaLing 2026)
%D 2026
%8 March
%I Association for Computational Linguistics
%C Rabat, Morocco
%@ 979-8-89176-367-8
%F storset-etal-2026-pain
%X This paper describes a new dataset for aspect-based sentiment analysis (ABSA) for analyzing patient feedback about healthcare services. In an interdisciplinary collaboration spanning the fields of natural language processing and healthcare research, we manually annotate a dataset of 2382 free-text comments collected from national patient experience surveys in Norway, covering two sub-fields of services – special mental healthcare and general practitioners. Annotations are provided on both the sentence- and comment-level, covering a fine-grained set of 25 unique healthcare-related aspects and their polarities. We also report results for fine-tuning both encoder- and decoder models on the resulting dataset, comparing different modeling strategies, like joint and sequential prediction of aspects and polarity. The resources developed in this work can assist healthcare researchers in the analysis of patient feedback, bringing a much more efficient approach compared to today’s manual analysis, potentially leading to improved patient satisfaction and clinical outcomes.
%U https://aclanthology.org/2026.healing-1.16/
%P 191-202
Markdown (Informal)
[From Pain to Praise: Aspect-Based Sentiment Analysis for Norwegian Patient Feedback](https://aclanthology.org/2026.healing-1.16/) (Storset et al., HeaLing 2026)
ACL