Cited by 341Social Robot Interaction and HRIAI in Service InteractionsSpeech and dialogue systems

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"I Hear You, I Feel You": Encouraging Deep Self-disclosure through a Chatbot

Lee, Yi-Chieh, Yamashita, Naomi, Huang, Yun, Fu, Wai·2020·Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

DOI 10.1145/3313831.3376175

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Abstract

Chatbots have great potential to serve as a low-cost, effective tool to support people's self-disclosure. Prior work has shown that reciprocity occurs in human-machine dialog; however, whether reciprocity can be leveraged to promote and sustain deep self-disclosure over time has not been systematically studied. In this work, we design, implement and evaluate a chatbot that has self-disclosure features when it performs small talk with people. We ran a study with 47 participants and divided them into three groups to use different chatting styles of the chatbot for three weeks. We found that chatbot self-disclosure had a reciprocal effect on promoting deeper participant self-disclosure that lasted over the study period, in which the other chat styles without self-disclosure features failed to deliver. Chatbot self-disclosure also had a positive effect on improving participants' perceived intimacy and enjoyment over the study period. Finally, we reflect on the design implications of chatbots where deep self-disclosure is needed over time.

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Nouraei, F., Rebello, K. J., Fallah, M., Murali, P., Matuszak, H., Jap, V., Parker, A. G., Paasche‐Orlow, M. K., & Bickmore, T. (2025) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3711101 · Cited by 10
Using Nonverbal Cues in Empathic Multi-Modal LLM-Driven Chatbots for Mental Health Support MHCI039
Schmidmaier, M., Rupp, J., Harrich, C., & Mayer, S. (2025) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3743724 · Cited by 10
“Such applications have been found to provide social and emotional support by showing interest and expressing empathy while encouraging self-disclosure through anonymity and non-judgmental behavior [15, 52, 63, 80].”
Can You Read Between the Lines?: A Comparison of Human and ChatGPT As Support Providers
Hwang, L. J., McKenzie, R., Feng, B., & Pan, W. (2025) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2025.2584724 · Cited by 11
“A few studies have found that chatbots can provide reciprocal self-disclosure during small talk with a conversational partner, improving perceived intimacy (Lee et al., 2020) or facilitating continued interaction with the chatbot (Bickmore et al., 2013).”
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Peltola, J., Kaipainen, K., Keinonen, K., Kiuru, N. H., & Turunen, M. (2023) · ACM Conference on Conversational User Interfaces (CUI) · doi:10.1145/3571884.3597142 · Cited by 12
“Moreover, prior research indicates that conversational agents that disclose information about themselves are better received by users, increasing engagement and self-disclosure [6, 31, 33].”
Background
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Goddard, Q., Moton, N., Hudson, J., & He, H. A. (2024) · Western Canadian Conference on Computing Education · doi:10.1145/3660650.3660662 · Cited by 9
Large Language Model Agents for Improving Engagement with Behavior Change Interventions: Application to Digital Mindfulness
Kumar, H., Yoo, S., Bernuy, A., Shi, J., Luo, H., Williams, J. J., Kuzminykh, A., Anderson, A., & Kornfield, R. (2024) · doi:10.2139/ssrn.4892998 · Cited by 9
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Mzwri, K., & Turcsányi-Szabó, M. (2023) · Central-European Journal of New Technologies in Research Education and Practice · doi:10.36427/cejntrep.5.1.5041 · Cited by 8
Examining the Content and Form of Supportive Conversations with Chatbots
Meng, J., Rains, S. A., Qin, J., & Rheu, M. (2025) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2025.2467450 · Cited by 8
“…that focused on aggregated linguistics features such as the number of positive/negative emotion words (Rains et al., 2020a, 2020b), word count, (Lee et al., 2020) and disclosure characteristics (e.g., disclosure intimacy, Ho et al., 2018; Lee et al., 2020) across supportive conversations with…”
Mining Evidence about Your Symptoms: Mitigating Availability Bias in Online Self-Diagnosis
Zhang, J., Zhu, Z., Li, J., & Lee, Y. (2025) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3713805 · Cited by 11
Self-citation
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Enhancing academic stress assessment through self-disclosure chatbots: effects on engagement, accuracy, and self-reflection
Park, M., Fels, S., & Seo, K. (2025) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-025-00527-z · Cited by 13
“In support of this idea, Lee et al. (2020) observed that chatbots sharing relatable challenges prompted reciprocal self-disclosure from users.”
Influential
Mental wellbeing effects of disclosing life events on social media
Saha, K., Yoo, D. W., Swain, V. D., & Choudhury, M. D. (2025) · Scientific Reports · doi:10.1038/s41598-025-07295-w · Cited by 11
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Cox, S. R., Jacobsen, R. M., & van Berkel, N. (2025) · ACM Conference on Conversational User Interfaces (CUI) · doi:10.1145/3719160.3736617 · Cited by 19
“Conversely, when Factual-disclosure came first, participants in the Familiar-condition experienced greater enjoyment and a stronger desire to continue.”
Influential
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Abbas, A., Wohn, C., Hu, D., Rho, E. H. R., & Lee, S. W. (2025) · ACM Conference on Conversational User Interfaces (CUI) · doi:10.1145/3719160.3736634 · Cited by 11
“Prior studies [71, 76, 101] suggest that agent’s self-disclosure can encourage reciprocal sharing from users.”
Grooming an ideal chatbot by training the algorithm: Exploring the exploitation of Replika users’ immaterial labor
Pan, S., Fortunati, L., & Edwards, A. P. (2025) · New Media & Society · doi:10.1177/14614448251338271 · Cited by 14
“Furthermore, Replika’s words normalize heavy self-disclosure and, based on norms of reciprocity for self-disclosure in close relationships (Lee et al., 2020), may further encourage User 16 to match the culture of relationship encouraged by Replika.”
Computational and ethical considerations for using large language models in psychotherapy
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Self-citation
Large Language Model Agents for Improving Engagement with Behavior Change Interventions: Application to Digital Mindfulness
Kumar, H., Yoo, S., Bernuy, A. Z., Shi, J., Luo, H., Williams, J. J., Kuzminykh, A., Anderson, A., & Kornfield, R. (2025) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3757619 · Cited by 24
Challenges and Opportunities for Interactive Technology to Support Parents of HIV-Positive Children in Ethiopia in the Disclosure Process
Bezabih, A. M., Gerling, K., Abebe, W., & Abeele, V. V. (2023) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3580756 · Cited by 10
“chatbots) facilitate self-disclosure [67, 68].”
Background
Beyond the Words: Analysis and Detection of Self-Disclosure Behavior during Robot Positive Psychology Interaction
Alghowinem, S., Jeong, S., Arias, K., Picard, R. W., Breazeal, C., & Park, H. W. (2021) · International Conference on Automatic Face and Gesture Recognition · doi:10.1109/fg52635.2021.9666969 · Cited by 8
Deep Learning Based Chatbot Framework for Mental Health Therapy
Bhagchandani, A., & Nayak, A. (2022) · Lecture notes in networks and systems · doi:10.1007/978-981-16-5689-7_24 · Cited by 9
”Mirror, Mirror, on the Wall” - Promoting Self-Regulated Learning using Affective States Recognition via Facial Movements
Chen, S., Liu, Y., Lu, R., Zhou, Y., Lee, Y., & Huang, Y. (2022) · Designing Interactive Systems Conference · doi:10.1145/3532106.3533500 · Cited by 10
“Research shows that conversational AI can promote users’ self-disclosure, which is also benefcial for users to refect more on their own behaviors [48, 54].”
BackgroundSelf-citation
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Nieminen, H., Vartiainen, A., Bond, R., Laukkanen, E., Mulvenna, M. D., & Kuosmanen, L. (2025) · Journal of Advanced Nursing · doi:10.1111/jan.16762 · Cited by 7
“Recommendations in the second group were more focused, targeting self-disclosure (Lee et al. 2020), conversational content (Kang et al. 2023; Lopatovska et al. 2022), balanced persuasion and trust (Haque and Rubya 2023) and interaction (Kang et al. 2023; Peltola et al. 2023), as well as…”
Characterizing Relationships with Companion and Assistant Large Language Models
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Chatbot Design Challenges and the Effect on User Behavior
Almutairi, S., Khan, S., Kuhail, M. A., & Taj, I. (2023) · Advances in web technologies and engineering book series · doi:10.4018/978-1-6684-6234-8.ch002 · Cited by 7
You Go First: The Effects of Self-Disclosure Reciprocity in Human-Chatbot Interactions
Croes, E. A. J., Antheunis, M. L., & He, L. (2023) · International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW) · doi:10.1109/aciiw59127.2023.10388091 · Cited by 8
“When self-disclosure is reciprocated, this creates a bond and a sense of solidarity [18] between a human and a chatbot.”
BackgroundInfluential
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Mühl, L., Stecker, L., Herter, E., Szczuka, J. M., Wischnewski, M., & Krämer, N. C. (2024) · Nordic Conference on Human-Computer Interaction · doi:10.1145/3679318.3685353 · Cited by 10
“Chatbots’ self-disclosure can trigger humans to disclose their personal feelings and thoughts [53].”
Apple Siri (input) + Voice Over (output) = a de facto marriage
Sayago, S., & Ribera, M. (2020) · International Conference on Software Development and Technologies for Enhancing Accessibility and Fighting Info-exclusion (DSAI) · doi:10.1145/3439231.3440603 · Cited by 7
“VAs research examines a large (and increasing) number of issues, including parenting [4], user satisfaction [25], anthropomorphism [18], [23], communication [22], [11], [5], [26], [19], privacy, trust and security [14], [10], design guidelines [21], [6], adoption [15], [29], emotional expressions [30], social presence…”
Background
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Iftikhar, Z., Ransom, S., Xiao, A., Nugent, N., & Huang, J. (2024) · arXiv · doi:10.48550/arxiv.2409.02244 · Cited by 6
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Köçeri, K., & KIRKKILIÇ, H. A. (2024) · Mersin Üniversitesi Eğitim Fakültesi Dergisi · doi:10.17860/mersinefd.1504250 · Cited by 6
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“Studies show that users prefer chatbots that present themselves transparently, avoiding overly anthropomorphic characteristics, which might elicit discomfort and reduce trust [59, 85].”
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Self-citation
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“LLMs, which generate responses based on vast datasets, enable more contextually relevant and adaptable interactions [25, 43].”
The Impact of Human-Likeness and Self-Disclosure on Message Acceptance in Virtual AI Influencers
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“In addition, self-disclosure by AI chatbots has been found to enhance the positive effects of providing emotional support to conversation partners [38], as well as increase perceived intimacy and enjoyment [31].”
Chatbots’ Empathetic Conversations and Responses: A Qualitative Study of Help‑Seeking Queries on Depressive Moods Across 8 Commercial Conversational Agents
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“Some studies have examined the interaction data between users and chatbots, but many have concentrated on machine learning–based autodetection [28] or have been limited to COVID-19 data [29,30].”
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Loerakker, M. B., Stefanidi, E., Niess, J., Mildner, T., & Woźniak, P. W. (2025) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3743718 · Cited by 6
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“It then invites each user to share recent hobbies, recreational activities, and fun facts about each other, while also disclosing information about itself to encourage reciprocal self-disclosure [90], “Even though I’m a chatbot, I absolutely love ‘traveling’ through the stories you share with me.””
Who will turn to chatbots for self-disclosure? Exploring conversation with chatbots, self-compassion, and existential meaninglessness in American and Hong Kong adolescents
Xie, W., Jen, E., Dougherty, A. W., Hu, H., Ho, W. S., & Cheung, H. N. (2025) · AI & Society · doi:10.1007/s00146-025-02771-3 · Cited by 8
Therapy as an NLP Task: Comparing LLMs and Human Peers Behaviors in CBT Sessions
Iftikhar, Z., Ransom, S., Xiao, A. W., Nugent, N. R., & Huang, J. J. S. (2026) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3817112 · Cited by 41
Eliciting User Self-disclosure using Reciprocity in Human-Voicebot Conversations
Harmsen, W., van Waterschoot, J., Hendrickx, I., & Theune, M. (2023) · ACM Conference on Conversational User Interfaces (CUI) · doi:10.1145/3571884.3604301 · Cited by 6
“The first finding is not in line with our expectations, since earlier studies have shown that self-disclosure by one conversation partner elicits self-disclosure by the other, both in human-human [2, 3] and human-machine interactions [12, 16, 17].”
BackgroundResult
User Preferences on AI Psychotherapy Based on Moderating Effects of Individual Personality Traits: Employing a Clustering Analysis
Lee, J., You, J. S., & Lee, D. (2024) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2024.2307695 · Cited by 8
“In previous AI chatbot research, users typically engaged in communication for around 10– 15 min (Lee et al., 2020; Pandey, Sharma, & Wazir, 2022; Stephens et al., 2019).”
Change gently: an agent-based virtual interview training for college students with great shyness
Geng, W., Zhou, C., & Bian, Y. (2024) · Virtual Reality · doi:10.1007/s10055-024-01076-y · Cited by 6
“Studies have shown that practicing interviews with a virtual agent as an interviewer is more effective in improving interview - ees’ skills and increasing self-disclosure compared to conventional methods (DeVault et al. 2014; Lucas et al. 2014, 2017; Lee et al. 2020; Damian et al. 2015).”
Conversational Survey Chatbot: User Experience and Perception
Đuka, I., & Njeguš, A. (2021) · International Scientific Conference Sinteza · doi:10.15308/sinteza-2021-322-327 · Cited by 6
Unifying Recommender Systems and Conversational User Interfaces
Starke, A. D., & Lee, M. (2022) · ACM Conference on Conversational User Interfaces (CUI) · doi:10.1145/3543829.3544524 · Cited by 8
“For example, in a mental health context, how much self-disclosure is evoked, whether an agent cares for a user, or if it asks to be taken care of, affects the flow of conversation and how the agent is perceived by the user [36, 43].”
Background
Discovering the Hidden Facts of User-Dispatcher Interactions via Text-based Reporting Systems for Community Safety
Liu, Y., Mayfield, R., & Huang, Y. (2023) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3579602 · Cited by 6
“An emotion-aware CA can quickly gain users’ trust and elicit more information from them [41], thus significantly improving the efficiency of information gathering during safety incidents.”
BackgroundSelf-citation

Authors: Lee, Y.-C., Yamashita, N., Huang, Y., & Fu, W.
Affiliations: University of Illinois Urbana-Champaign (US)
NTT (Japan) (JP)
ORCID: Lee, Yi-Chieh
Yamashita, Naomi
Huang, Yun
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems
Publisher: ACM
Published: 2020-04-21
Pages: 1-12
DOI: 10.1145/3313831.3376175
OpenAlex: W3029922759
Cited by: 339
References: 39
Citations by year: 2026: 52 · 2025: 86 · 2024: 60 · 2023: 58 · 2022: 45 · 2021: 32 · 2020: 6
FWCI: 49.75
Type: conference paper
Language: en
Open access: closed
Licence: www.acm.org/publications/policies/copyright_policy#Background (vor)
Locations: CHI Conference on Human Factors in Computing Systems (publishedVersion)
Funders: Japan Society for the Promotion of Science (Scientific Research (A) 17H00771)
Topics: Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
Social Sciences › Business, Management and Accounting › Marketing › AI in Service Interactions
Physical Sciences › Computer Science › Artificial Intelligence › Speech and dialogue systems
Keywords: chatbots, self-disclosure, reciprocity, human-computer dialogue, small talk, intimacy, enjoyment, chatbot design, long-term interaction

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"I Hear You, I Feel You": Encouraging Deep Self-disclosure through a Chatbot

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