@inproceedings{chen-etal-2023-uncivil,
title = "The uncivil empathy: Investigating the relation between empathy and toxicity in online mental health support forums",
author = "Chen, Ming-Bin and
Lau, Jey Han and
Frermann, Lea",
editor = "Muresan, Smaranda and
Chen, Vivian and
Casey, Kennington and
David, Vandyke and
Nina, Dethlefs and
Koji, Inoue and
Erik, Ekstedt and
Stefan, Ultes",
booktitle = "Proceedings of the 21st Annual Workshop of the Australasian Language Technology Association",
month = nov,
year = "2023",
address = "Melbourne, Australia",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.alta-1.16",
pages = "136--147",
abstract = "We explore the relationship between empathy and toxicity in the context of online mental health forums. Despite the common assumption of a negative correlation between these concepts, it has not been empirically examined. We augment the EPITOME mental health empathy dataset with toxicity labels using two widely employed toxic/harmful content detection APIs: Perspective API and OpenAI moderation API. We find a notable presence of toxic/harmful content (17.77{\%}) within empathetic responses, and only a very weak negative correlation between the two variables. Qualitative analysis revealed contributions labeled as empathetic often contain harmful content such as promotion of suicidal ideas. Our results highlight the need for reevaluating empathy independently from toxicity in future research and encourage a reconsideration of empathy{'}s role in natural language generation and evaluation.",
}
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%0 Conference Proceedings
%T The uncivil empathy: Investigating the relation between empathy and toxicity in online mental health support forums
%A Chen, Ming-Bin
%A Lau, Jey Han
%A Frermann, Lea
%Y Muresan, Smaranda
%Y Chen, Vivian
%Y Casey, Kennington
%Y David, Vandyke
%Y Nina, Dethlefs
%Y Koji, Inoue
%Y Erik, Ekstedt
%Y Stefan, Ultes
%S Proceedings of the 21st Annual Workshop of the Australasian Language Technology Association
%D 2023
%8 November
%I Association for Computational Linguistics
%C Melbourne, Australia
%F chen-etal-2023-uncivil
%X We explore the relationship between empathy and toxicity in the context of online mental health forums. Despite the common assumption of a negative correlation between these concepts, it has not been empirically examined. We augment the EPITOME mental health empathy dataset with toxicity labels using two widely employed toxic/harmful content detection APIs: Perspective API and OpenAI moderation API. We find a notable presence of toxic/harmful content (17.77%) within empathetic responses, and only a very weak negative correlation between the two variables. Qualitative analysis revealed contributions labeled as empathetic often contain harmful content such as promotion of suicidal ideas. Our results highlight the need for reevaluating empathy independently from toxicity in future research and encourage a reconsideration of empathy’s role in natural language generation and evaluation.
%U https://aclanthology.org/2023.alta-1.16
%P 136-147
Markdown (Informal)
[The uncivil empathy: Investigating the relation between empathy and toxicity in online mental health support forums](https://aclanthology.org/2023.alta-1.16) (Chen et al., ALTA 2023)
ACL