English

Mixed Feelings: Cross-Domain Sentiment Classification of Patient Feedback

Computation and Language 2025-02-03 v1

Abstract

Sentiment analysis of patient feedback from the public health domain can aid decision makers in evaluating the provided services. The current paper focuses on free-text comments in patient surveys about general practitioners and psychiatric healthcare, annotated with four sentence-level polarity classes -- positive, negative, mixed and neutral -- while also attempting to alleviate data scarcity by leveraging general-domain sources in the form of reviews. For several different architectures, we compare in-domain and out-of-domain effects, as well as the effects of training joint multi-domain models.

Keywords

Cite

@article{arxiv.2501.19134,
  title  = {Mixed Feelings: Cross-Domain Sentiment Classification of Patient Feedback},
  author = {Egil Rønningstad and Lilja Charlotte Storset and Petter Mæhlum and Lilja Øvrelid and Erik Velldal},
  journal= {arXiv preprint arXiv:2501.19134},
  year   = {2025}
}

Comments

Accepted for NoDaLiDa / Baltic-HLT 2025