The Language of Situational Empathy

Ke Zhou, Luca Maria Aiello, Sanja Scepanovic, Daniele Quercia, Sarah Konrath

Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review

Abstract

Empathy is the tendency to understand and share others' thoughts and feelings. Literature in psychology has shown through surveys potential beneficial implications of empathy. Prior psychology literature showed that a particular type of empathy called "situational empathy" --- an immediate empathic response to a triggering situation (e.g., a distressing situation) --- is reflected in the language people use in response to the situation. However, this has not so far been properly measured at scale. In this work, we collected 4k textual reactions (and corresponding situational empathy labels) to different stories. Driven by theoretical concepts, we developed computational models to predict situational empathy from text and, in so doing, we built and made available a list of empathy-related words. When applied to Reddit posts and movie transcripts, our models produced results that matched prior theoretical findings, offering evidence of external validity and suggesting its applicability to unstructured data. The capability of measuring proxies for empathy at scale might benefit a variety of areas such as social media, digital healthcare, and workplace well-being.
Original languageEnglish
Title of host publicationProceedings of the ACM on Human-Computer Interaction
Number of pages19
Volume5
PublisherACM Conference on Computer-Human Interaction
Publication date22 Apr 2021
Edition1
Pages1-19
DOIs
Publication statusPublished - 22 Apr 2021

Keywords

  • Empathy
  • Situational Empathy
  • Text Analysis
  • Computational Modeling
  • Natural Language Processing (NLP)

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