Show Me You Care

Otterbacher, Jahna; Ang, Chee Siang; Litvak, Marina; Atkins, David C.

doi:10.1145/2996188

Cited by 18 publications

(3 citation statements)

References 54 publications

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“…Most of the research on empathy detection has focused on spoken conversations or interactions, some in online platforms (e.g. (Pérez-Rosas et al, 2017;Khanpour et al, 2017;Otterbacher et al, 2017;Sharma et al, 2021;Hosseini and Caragea, 2021), very little on narrative genre (Buechel et al, 2018;Wambsganss et al, 2021), and even less in clinical settings. Buechel et al (2018) used crowdsourced workers to self-report their empathy and distress levels and to write empathic reactions to news stories.…”

Section: Related Workmentioning

confidence: 99%

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

Dey¹,

Gîrju²

2023

Preprint

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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 firstperson narrative essays.

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Section: Related Workmentioning

confidence: 99%

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

Dey¹,

Gîrju²

2023

Preprint

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“…Therefore, use to emotionalize, informal and less complex language styles can positively influence consumer engagement. Otterbacher et al, (2017) found that informal communication styles can be used to soften hierarchical power relations, reduce social distance, and convey a sense of intimacy.…”

Section: Language Stylementioning

confidence: 99%

How to Promote Public Engagement and Enhance Sentiment Through Government Social Media During the COVID-19 Crisis

Shi

et al. 2022

Journal of Organizational and End User Computing

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In the period of public health crisis, effective and efficient transmission of crisis information to the public through social media is an important support for achieving social stability and orderly online public engagement. From the perspective of public value management, this study systematically investigated how local government agencies in China used social media to promote public engagement and raise public sentiment during the COVID-19 crisis. Using data captured from the “Wuhan Release” Sina Weibo account, the authors studied the factors that influence public engagement, including information sources, language styles, and media types. Further, it explores the influence of the interactive effects of public value with information sources, language styles, and media types on public engagement and public sentiment. The results show that the consistency of government response content and public value promotes public engagement and raises public sentiment. This research provides enlightenment and ideas for cognition, understanding and governance of public opinion in practice.

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“…Most of the research on empathy detection has focused on conversations or interactions, as dialogue systems Chen et al, 2022a;Samad et al, 2022), or in online platforms (e.g. (Pérez-Rosas et al, 2017;Khanpour et al, 2017;Otterbacher et al, 2017;Sharma et al, 2020;Lahnala et al, 2022;Sharma et al, 2021;Hosseini and Caragea, 2021), a few on news stories and other narratives (Buechel et al, 2018;Wambsganss et al, 2021b;Sedoc et al, 2020;Mundra et al, 2021;Guda et al, 2021), and even less on empathy in clinical settings Shi et al, 2021). Buechel et al (2018) used crowd-sourced workers to self-report their empathy and distress levels and to write empathic reactions to news stories.…”

Section: Related Workmentioning

confidence: 99%

Proceedings of the 13th International Workshop on Health Text Mining and Information Analysis (LOUHI)

Velupillai¹,

Duneld²,

Henriksson³

et al. 2022

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Show Me You Care

Abstract: The version in the Kent Academic Repository may differ from the final published version. Users are advised to check http://kar.kent.ac.uk for the status of the paper. Users should always cite the published version of record.

Cited by 18 publications

References 54 publications

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

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

How to Promote Public Engagement and Enhance Sentiment Through Government Social Media During the COVID-19 Crisis

Proceedings of the 13th International Workshop on Health Text Mining and Information Analysis (LOUHI)

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