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Chatbot as an emergency exist: Mediated empathy for resilience via human-AI interaction during the COVID-19 pandemic
Open accessAbstract
As a global health crisis, the COVID-19 pandemic has also made heavy mental and emotional tolls become shared experiences of global communities, especially among females who were affected more by the pandemic than males for anxiety and depression. By connecting multiple facets of empathy as key mechanisms of information processing with the communication theory of resilience, the present study examines human-AI interactions during the COVID-19 pandemic in order to understand digitally mediated empathy and how the intertwining of empathic and communicative processes of resilience works as coping strategies for COVID-19 disruption. Mixed methods were adopted to explore the using experiences and effects of Replika, a chatbot companion powered by AI, with ethnographic research, in-depth interviews, and grounded theory-based analysis. Findings of this research extend empathy theories from interpersonal communication to human-AI interactions and show five types of digitally mediated empathy among Chinese female Replika users with varying degrees of cognitive empathy, affective empathy, and empathic response involved in the information processing processes, i.e., companion buddy, responsive diary, emotion-handling program, electronic pet, and tool for venting. When processing information obtained from AI and collaborative interactions with the AI chatbot, multiple facets of mediated empathy become unexpected pathways to resilience and enhance users' well-being. This study fills the research gap by exploring empathy and resilience processes in human-AI interactions. Practical implications, especially for increasing individuals' psychological resilience as an important component of global recovery from the pandemic, suggestions for future chatbot design, and future research directions are also discussed.
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Metadata
- Authors
- Jiang, Q., Zhang, Y., & Pian, W.
- Affiliations
- Tsinghua University (CN)
- Wuhan University (CN)
- Corresponding author
- Pian, Wenjing
- Venue
- Information Processing & Management
- Publisher
- Elsevier BV
- Published
- 2022-11
- Volume
- 59
- Issue
- 6
- Pages
- 103074
- ISSN
- 0020-0271 (ISSN-L)
- 0306-4573
- PMC
- PMC9428597
- OpenAlex
- W4293745145
- Cited by
- 165
- References
- 94
- Citations by year
- 2026: 47 · 2025: 59 · 2024: 30 · 2023: 25 · 2022: 4
- FWCI
- 25.11
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- Locations
- Information Processing & Management (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Natural Science Foundation of China (71904028)
- National Office for Philosophy and Social Sciences (18ZDA307)
- Topics
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Keywords
- chatbots, human-AI interaction, psychological resilience, COVID-19 pandemic, Replika, cognitive empathy, affective empathy, female users, mental health, coping strategies, chatbot design, Chinese users
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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