The Language of Situational Empathy

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

Publikation: Konference artikel i Proceeding eller bog/rapport kapitelKonferencebidrag i proceedingsForskningpeer 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.
OriginalsprogEngelsk
TitelProceedings of the ACM on Human-Computer Interaction
Antal sider19
Vol/bind5
ForlagACM Conference on Computer-Human Interaction
Publikationsdato22 apr. 2021
Udgave1
Sider1-19
DOI
StatusUdgivet - 22 apr. 2021

Emneord

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

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