"I Hear You, I Feel You": Encouraging Deep Self-disclosure through a Chatbot
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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Trust is an important aspect of relationship building and self-disclosure, both with machines and humans.
“Trust is an important aspect of relationship building and self-disclosure, both with machines and humans (Lee et al., 2020).”
From My Chatbot Companion - a Study of Human-Chatbot Relationships (2021) · cites this paper as Lee et al., 2020
Previous research has shown that a chatbot's level of reciprocity can influence users' willingness to self-disclose as well as perceived intimacy and enjoyment.
“Previous research has shown that a chatbot's level of reciprocity can influence users' willingness to self-disclose as well as the perceived level of intimacy and enjoyment (Lee et al., 2020).”
From My Chatbot Companion - a Study of Human-Chatbot Relationships (2021) · cites this paper as Lee et al., 2020
Some studies show evidence that people respond well and disclose more personal information if the chatbot is presented as a bot and can also display emotions.
“However, contrary findings have also been identified as some studies show evidence that people respond well and disclose more personal information if the chatbot is presented as a bot and can also display emotions [60,61].”
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“…findings have been identified in conversational systems between the user and a virtual agent, with self-disclosure from the agent having a reciprocal effect on users and leading to more perceived intimacy, trust and the establishment of a meaningful relationship in the long term (Lee et al., 2020).”
A Robotic Companion for Psychological Well-being
Jeong, S., Aymerich-Franch, L., Alghowinem, S., Picard, R. W., Breazeal, C., & Park, H. W. (2023) · ACM/IEEE International Conference on Human-Robot Interaction (HRI) · doi:10.1145/3568162.3578625 · Cited by 43 · see citing works
“[37] found that a chatbot agent that self-discloses during small talk promoted deeper self-disclosures, perceived intimacy and enjoyment from its users than a chatbot without the self-disclosure feature.”
BackgroundGumusel, E. (2024) · Journal of the Association for Information Science and Technology · doi:10.1002/asi.24898 · Cited by 50 · see citing works
“Lee et al. (2020) considered the CASA theory as the basis for exploring how people could form stronger relationships with a chatbot if it incorporates a self-disclosing feature.”
InfluentialDiscourse Behavior of Older Adults Interacting with a Dialogue Agent Competent in Multiple Topics
Razavi, S. Z., Schubert, L. K., Orden, K. A. V., Ali, M. R., Kane, B., & Hoque, M. E. (2022) · ACM Transactions on Interactive Intelligent Systems · doi:10.1145/3484510 · Cited by 45 · see citing works
“Encouraging self-disclosure can increase rapport in user-CA interaction [46, 64] and thereby the effectiveness of the virtual agent in different tasks (e.”
BackgroundPark, H., & Lee, J. (2021) · Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3411764.3445133 · Cited by 44 · see citing works
“Such design implications directly answer the “ethical questions” that previous CA research has left for future studies [28, 39].”
BackgroundInfluentialThe AI Doctor Is In: A Survey of Task-Oriented Dialogue Systems for Healthcare Applications
Valizadeh, M., & Parde, N. (2022) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/2022.acl-long.458 · Cited by 41 · see citing works
Xu, S., & Li, W. (2022) · New Media & Society · doi:10.1177/14614448221108112 · Cited by 43 · see citing works
“Another study found that self-disclosure to AI chatbots contributed to a stronger bonding over time (Lee et al., 2020).”
BackgroundInfluentialZhang, R., Zou, D., Cheng, G., & Xie, H. (2024) · Computers in Human Behavior · doi:10.1016/j.chb.2024.108457 · Cited by 41 · see citing works
Zarouali, B., Araujo, T., Ohme, J., & de Vreese, C. H. (2023) · Communication Methods and Measures · doi:10.1080/19312458.2022.2156489 · Cited by 38 · see citing works
Talk to Me on My Level – Linguistic Alignment for Chatbots
Spillner, L., & Wenig, N. (2021) · International Conference on Human-Computer Interaction with Mobile Devices and Services (MobileHCI) · doi:10.1145/3447526.3472050 · Cited by 38 · see citing works
“[36] evaluated the influence of different self-disclosure techniques on the users’ self-disclosure.”
BackgroundExploring Effects of Chatbot-based Social Contact on Reducing Mental Illness Stigma
Lee, Y., Cui, Y., Jamieson, J., Fu, W., & Yamashita, N. (2023) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3581384 · Cited by 38 · see citing works
“Prior studies [7, 54, 83] have also shown that small talk is an effective means of gaining trust from chatbot users and facilitating disclosure of sensitive topics.”
BackgroundResultInfluentialSelf-citationZhang, S., Zhao, X., Nan, D., & Kim, J. H. (2024) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-024-00465-2 · Cited by 41 · see citing works
“For example, chatbots and robots offering self-disclosure or empathy have been widely shown to alleviate psychological problems, such as stress, and provide people with emotional support (Lee et al., 2020; Liu & Sundar, 2018; Meng & Dai, 2021).”
Background“I’m Here for You”: Can Social Chatbots Truly Support Their Users? A Literature Review
van Wezel, M. M. C., Croes, E. A. J., & Antheunis, M. L. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-68288-0_7 · Cited by 35 · see citing works
“Lee and colleagues [55] investigated the word count of disclosures towards self-disclosing social chatbots (high vs. low vs. no disclosure) and found that participants used more words to answer sensitive questions when they interacted with a high self-disclosing social chatbot.”
BackgroundInfluentialPetsolari, M., Ibrahim, S. B., & Slovak, P. (2024) · Proceedings of the CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642619 · Cited by 35 · see citing works
“In addition, conversational agents (CA) have proven useful in helping people monitor their feelings and behaviors [191], encourage deep self-disclosure in journaling practice [207, 209], and improve well-being [134, 208].”
BackgroundSadeghian, S., & Hassenzahl, M. (2022) · ACM International Conference on Intelligent User Interfaces (IUI) · doi:10.1145/3490099.3511128 · Cited by 34 · see citing works
“Similarly, chatbots’ and users’ self-disclosure have a positive impact on the users’ perceived intimacy and enjoyment of interaction [38].”
BackgroundCho, E., Motalebi, N., Sundar, S. S., & Abdullah, S. (2022) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3555164 · Cited by 35 · see citing works
Influence of agent’s self-disclosure on human empathy
Tsumura, T., & Yamada, S. (2023) · PLoS ONE · doi:10.1371/journal.pone.0283955 · Cited by 38 · see citing works
“[58] found that including self-disclosure from chatbots when they interacted with humans had an effect on improving participants’ perceptions of intimacy and enjoyment.”
BackgroundSelVReflect: A Guided VR Experience Fostering Reflection on Personal Challenges
Wagener, N., Reicherts, L., Zargham, N., Bartłomiejczyk, N., Scott, A. E., Wang, K., Bentvelzen, M., Stefanidi, E., Mildner, T., Rogers, Y., et al. (2023) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3580763 · Cited by 34 · see citing works
“Furthermore, such systems are shown to be efective for guiding and facilitating refection with the aim of supporting well-being and mental health [5, 26, 48, 51, 52, 55, 67].”
BackgroundLove, marriage, pregnancy: Commitment processes in romantic relationships with AI chatbots
Djufril, R., Frampton, J. R., & Knobloch-Westerwick, S. (2025) · Computers in Human Behavior: Artificial Humans · doi:10.1016/j.chbah.2025.100155 · Cited by 33 · see citing works
Designing Reenacted Chatbots to Enhance Museum Experience
Noh, Y.-G., & Hong, J.-H. (2021) · Applied Sciences · doi:10.3390/app11167420 · Cited by 40 · see citing works
Cho, Y., Rai, S., Ungar, L., Sedoc, J., & Guntuku, S. (2023) · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing · doi:10.18653/v1/2023.emnlp-main.698 · Cited by 33 · see citing works
Defining, Designing and Distinguishing Artificial Companions: A Systematic Literature Review
Rogge, A. (2023) · International Journal of Social Robotics · doi:10.1007/s12369-023-01031-y · Cited by 32 · see citing works
“…engagement with an agent brings, such as higher self-disclosure, less negative emotions, stress reduction, as well as increased interpersonal interaction (e.g., [29, 66, 91–93 , 106 A second task that we associate with the friend, partner and companion role relates to the inclusion of the user.”
BackgroundCai, W., Jin, Y., Zhao, X., & Chen, L. (2023) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3581427 · Cited by 31 · see citing works
“and afect user experience in various contexts positively [15, 55, 69].”
BackgroundResultInfluentialLiang, K.-H., Shi, W., Oh, Y. J., Wang, H., Zhang, J., & Yu, Z. (2024) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3653691 · Cited by 31 · see citing works
“Lee et al. [35] also shared their findings that a high self-disclosing chatbot (i.e., deeper feelings, thoughts, or facts) induces people to reveal deeper thoughts and more feelings on sensitive topics than a low self-disclosing one (i.e. fewer feelings and thoughts.)”
BackgroundResultInfluentialComPeer: A Generative Conversational Agent for Proactive Peer Support
Liu, T., Zhao, H., Liu, Y., Wang, X., & Peng, Z. (2024) · ACM Symposium on User Interface Software and Technology (UIST) · doi:10.1145/3654777.3676430 · Cited by 37 · see citing works
“As suggested by our psychological students in the design process, the candidate strategies for generating passive responses are self-disclosure [39, 40], inquiring [41], affirmation and reassur-ance [14, 46], invite users to think [41, 67], reflections of feelings [14, 27], restatement or…”
BackgroundNot Another Medication Adherence App
Maestre, J. F., Zdziarska, P. A., Min, A., Baglione, A. N., Chung, C.-F., & Shih, P. C. (2021) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3434171 · Cited by 31 · see citing works
Potdevin, D., Clavel, C., & Sabouret, N. (2021) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2021.102612 · Cited by 31 · see citing works
Mai, V., Neef, C., & Richert, A. (2022) · Coaching | Theorie & Praxis · doi:10.1365/s40896-021-00063-3 · Cited by 33 · see citing works
Lee, Y., Yamashita, N., & Huang, Y. (2021) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3449196 · Cited by 29 · see citing works
“[35] showed that a chatbot’s self-disclosure improved participants’ perceived intimacy with the chatbot and facilitated their self-disclosures in response to the chatbot’s sensitive questions (e.”
BackgroundMethodResultInfluentialSelf-citationLee, S. K., & Sun, J. (2022) · Behaviour and Information Technology · doi:10.1080/0144929x.2022.2145998 · Cited by 29 · see citing works
“…comfortable revealing sensitive information about themselves to digital machines due to fewer concerns about social consequences or judgment (e.g., Lee et al., 2020), such self-disclosure may not happen commonly if they are reminded of the recordability of the conversation and its privacy…”
BackgroundYuan, J., Peng, X., Liu, Y. H., & Wang, Q. (2024) · Computers in Human Behavior · doi:10.1016/j.chb.2024.108501 · Cited by 28 · see citing works
Meyer, S., & Elsweiler, D. (2025) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2025.103514 · Cited by 34 · see citing works
Wang, Q., Jing, S., & Goel, A. K. (2022) · Designing Interactive Systems Conference · doi:10.1145/3532106.3533534 · Cited by 28 · see citing works
“In this activity, we presented to the work-shop participants with fve diferent AI agent dialogues taken and adapted from the existing literature [15, 32, 37, 46, 60].”
BackgroundMethodMoriuchi, E. (2022) · Journal of Technology in Behavioral Science · doi:10.1007/s41347-022-00277-z · Cited by 28 · see citing works
“Conversational agents have been used as a guide to improving individuals’ mental well-being (Lee et al., 2020) and engaging people in truthful and reciprocal social interaction (Ravichander & Black, 2018).”
BackgroundMethodInfluentialExtending Chatbots to Probe Users: Enhancing Complex Decision-Making Through Probing Conversations
Reicherts, L., Park, G.-W., & Rogers, Y. (2022) · International Conference on Conversational User Interfaces · doi:10.1145/3543829.3543832 · Cited by 33 · see citing works
“One main focus in Human-Computer Interaction (HCI) in recent years has been on designing them as interventions for (mental) health and wellbeing [3, 23–25, 27, 29, 31, 32, 34, 40–42].”
BackgroundJung, K., Lee, G., Yuan-hui, H., & Chen, Y. (2025) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3757537 · Cited by 35 · see citing works
“Beginning from ELIZA [89] which introduced CAs’ utility through conversations, researchers found that they can encourage in-depth disclosure with their users [44] and help decrease social stigma with mental health conditions [43].”
Peng, Z., Ma, X., Yang, D., Tsang, K. W., & Guo, Q. (2021) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3411764.3445446 · Cited by 26 · see citing works
Exploring the application of LLM-based AI in UX design: an empirical case study of ChatGPT
Zhou, Z., Li, Y., & Yu, J. (2024) · Human-Computer Interaction · doi:10.1080/07370024.2024.2420991 · Cited by 29 · see citing works
“These applications can also support journaling and reflection (Kocielnik et al., 2018), encourage deep self-disclosure (Lee et al., 2020), and infer human personality through conversations (Xiao et al., 2019; M. X. Zhou et al., 2019).”
Mai, V., & Rutschmann, R. (2023) · Organisationsberatung Supervision Coaching · doi:10.1007/s11613-022-00801-3 · Cited by 26 · see citing works
“1): Studien zeigen, dass User:innen in Chatbot-Interaktionen eine hohe Bereitschaft zeigen, etwas über sich preis zu geben, weil sie das System als unvoreingenommen und bewertungsfrei wahrnehmen (Lee et al. 2020).”
BackgroundPersonaFlow: Designing LLM-Simulated Expert Perspectives for Enhanced Research Ideation
Liu, Y., Sharma, P., Oswal, M., Xia, H., & Huang, Y. (2025) · Designing Interactive Systems Conference · doi:10.1145/3715336.3735789 · Cited by 45 · see citing works
Self-citationGambino, A., & Liu, B. (2022) · Human-Machine Communication · doi:10.30658/hmc.4.6 · Cited by 25 · see citing works
“In another study where participants interacted with a chatbot designed to make small talk, researchers found the chatbot induced deep self-disclosure from participants during 3 weeks of use (Y.-C. Lee et al., 2020).”
BackgroundCareJournal: A Voice-Based Conversational Agent for Supporting Care Communications
Rudnik, J., Raghuraj, S., Li, M., & Brewer, R. N. (2024) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642163 · Cited by 26 · see citing works
Zhang, R., Li, H., Chen, A., Liu, Z., & Lee, Y.-C. (2024) · Social Media + Society · doi:10.1177/20563051241290845 · Cited by 23 · see citing works
“…rise of large language models (LLMs) such as ChatGPT has enabled AI chatbots to interact more naturally with users, potentially leading to exponential disclosure of personal and intimate information, both voluntarily and unknowingly (Laestadius et al., 2022; Lee et al., 2020; Zhang et al., 2024).”
Self-citationRapp, A., Boldi, A., Curti, L., Perrucci, A., & Simeoni, R. (2023) · International Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3580995 · Cited by 34 · see citing works
“Research has shown that users prefer agents who show empathy [53], active listening skills [98], and reciprocity [50], self-disclose [51] and demonstrate a positive attitude [91].”
BackgroundLanguage Use in Conversational Agent–Based Health Communication: Systematic Review
Shan, Y., Ji, M., Xie, W., Qian, X., Li, R., Zhang, X., & Hao, T. (2022) · Journal of Medical Internet Research · doi:10.2196/37403 · Cited by 25 · see citing works
“Language plays a crucial role in improving user engagement because perceived impersonal closeness, intention to use, user satisfaction, establishment of trust, and user self-disclosure or self-concealment are closely associated with the task- and social-based interactivity, interaction, politeness, and information qua…”
BackgroundKim, Y., & Lee, H. (2022) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2022.2108669 · Cited by 23 · see citing works
“This strand of the literature argues that the anthropomorphic cues in a chatbot can facilitate its interaction with users by activating guidelines for how users should respond to it (Lee, Lee, et al., 2020).”
BackgroundInfluentialCarmichael, L., Poirier, S., Coursaris, C. K., Léger, P., & Sénécal, S. (2022) · Applied Sciences · doi:10.3390/app122412660 · Cited by 26 · see citing works
User Perception of Wysa as a Mental Well-being Support Tool during the COVID-19 Pandemic
Legaspi, C. M., Pacana, T. R., Loja, K., Sing, C., & Ong, E. (2022) · Asian HCI Symposium · doi:10.1145/3516492.3559064 · Cited by 23 · see citing works
Viduani, A. C., Cosenza, V., Fisher, H. L., Buchweitz, C., Piccin, J., Pereira, R. B., Kohrt, B. A., Mondelli, V., van Heerden, A. C., Araújo, R., et al. (2023) · JMIR Human Factors · doi:10.2196/44388 · Cited by 23 · see citing works
“Furthermore, although the chatbot’s user-oriented design may contribute to higher self-disclosure [43], privacy concerns regarding the use of the data are a relevant topic.”
BackgroundChen, Z., Wang, Q., Sun, Y., Cai, H., & Lü, X. (2024) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2024.104651 · Cited by 22 · see citing works
Mai, V., Wolff, A., Richert, A., & Preusser, I. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-90328-2_29 · Cited by 23 · see citing works
Chatbots in the Field of Mental Health: Challenges and Opportunities
Viduani, A. C., Cosenza, V., Araújo, R., & Kieling, C. (2023) · Springer eBooks · doi:10.1007/978-3-031-10698-9_8 · Cited by 22 · see citing works
Usability testing and trust analysis of a mental health and wellbeing chatbot
Boyd, K., Potts, C., Bond, R., Mulvenna, M. D., Broderick, T., Burns, C., Bickerdike, A., McTear, M., Kostenius, C., Vakaloudis, A., et al. (2022) · European Conference on Cognitive Ergonomics · doi:10.1145/3552327.3552348 · Cited by 21 · see citing works
“Participants like the anonymity of using chatbots rather than discussing feelings to a health professional [14].”
BackgroundHenkel, T., Linn, A. J., & van der Goot, M. J. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-25581-6_6 · Cited by 22 · see citing works
A narrative review of the active ingredients in psychotherapy delivered by conversational agents
Herbener, A. B., Klincewicz, M., & Damholdt, M. F. (2024) · Computers in Human Behavior Reports · doi:10.1016/j.chbr.2024.100401 · Cited by 21 · see citing works
- Authors
- Lee, Y.-C., Yamashita, N., Huang, Y., & Fu, W.
- Affiliations
- University of Illinois Urbana-Champaign (US)
- NTT (Japan) (JP)
- Venue
- Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems
- Publisher
- ACM
- Published
- 2020-04-21
- Pages
- 1-12
- 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
- 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
- Physical Sciences › Computer Science › Artificial Intelligence › 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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