Investigating Stylistic Profiles for the Task of Empathy Classification in Medical Narrative Essays

Priyanka Dey, Roxana Girju

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

One important aspect of language is how speakers generate utterances and texts to convey their intended meanings. In this paper, we bring various aspects of the Construction Grammar (CxG) and the Systemic Functional Grammar (SFG) theories in a deep learning computational framework to model empathic language. Our corpus consists of 440 essays written by premed students as narrated simulated patient–doctor interactions. We start with baseline classifiers (state-of-the-art recurrent neural networks and transformer models). Then, we enrich these models with a set of linguistic constructions proving the importance of this novel approach to the task of empathy classification for this dataset. Our results indicate the potential of such constructions to contribute to the overall empathy profile of first-person narrative essays.

Original languageEnglish (US)
Title of host publicationCxGsNLP 2023 - 1st International Workshop on Construction Grammars and NLP (CxGs+NLP, GURT/SyntaxFest 2023), Proceedings of the Conference
PublisherAssociation for Computational Linguistics
Pages63-74
Number of pages12
ISBN (Electronic)9781959429357
StatePublished - 2023
Externally publishedYes
Event1st International Workshop on Construction Grammars and NLP (CxGs+NLP, GURT/SyntaxFest 2023), CxGsNLP 2023 - Virtual, Online
Duration: Mar 9 2023Mar 12 2023

Publication series

NameCxGsNLP 2023 - 1st International Workshop on Construction Grammars and NLP (CxGs+NLP, GURT/SyntaxFest 2023), Proceedings of the Conference

Conference

Conference1st International Workshop on Construction Grammars and NLP (CxGs+NLP, GURT/SyntaxFest 2023), CxGsNLP 2023
CityVirtual, Online
Period3/9/233/12/23

ASJC Scopus subject areas

  • Language and Linguistics
  • Computational Theory and Mathematics
  • Computer Science Applications
  • Information Systems

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