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"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 (Lee et al., 2020).”
From My Chatbot Companion - a Study of Human-Chatbot Relationships (2021) · cites this paper as Lee et al., 2020
In the citing paper
“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
In the citing paper
“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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My Chatbot Companion - a Study of Human-Chatbot Relationships
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“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).”
BackgroundRapp, A., Curti, L., & Boldi, A. (2021) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2021.102630 · Cited by 733
My AI Friend: How Users of a Social Chatbot Understand Their Human–AI Friendship
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Zhang, J., Oh, Y. J., Lange, P., Yu, Z., & Fukuoka, Y. (2020) · Journal of Medical Internet Research · doi:10.2196/22845 · Cited by 363
“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].”
ResultA longitudinal study of human–chatbot relationships
Skjuve, M., Følstad, A., Fostervold, K. I., & Brandtzaeg, P. B. (2022) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2022.102903 · Cited by 253
“Previous chatbot research has also highlighted the importance of the chatbot being empathic as well as providing mutuality in self-disclosure (Lee et al., 2020).”
BackgroundResultInfluentialSocial companionship with artificial intelligence: Recent trends and future avenues
Chaturvedi, R., Verma, S., Das, R., & Dwivedi, Y. K. (2023) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2023.122634 · Cited by 244
Friend, mentor, lover: does chatbot engagement lead to psychological dependence?
Xie, T., Pentina, I., & Hancock, T. (2023) · Journal of Service Management · doi:10.1108/josm-02-2022-0072 · Cited by 204
Lee, Y., Yamashita, N., & Huang, Y. (2020) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3392836 · Cited by 195
“…people revealed deeper thoughts and more feelings on sensitive topics (e.g., social and sexual relationships, experiences of failure, causes of stress and anxiety) with a high self-disclosing chatbot over time than with chatbots that either did not self-disclose or disclosed less with people [51].”
BackgroundSelf-citationPentina, I., Xie, T., Hancock, T. D., & Bailey, A. A. (2023) · Psychology and Marketing · doi:10.1002/mar.21853 · Cited by 214
Chin, H., Song, H., Baek, G., Shin, M., Jung, C., Cha, M., Choi, J., & Cha, C. (2023) · Journal of Medical Internet Research · doi:10.2196/51712 · Cited by 213
“Similarly, studies focusing on chatbots designed to promote user self-disclosure have found that chatbots that offer detailed, self-disclosed responses tend to encourage greater self-disclosure from their users [63].”
Jo, E., Epstein, D. A., Jung, H., & Kim, Y.-H. (2023) · Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3581503 · Cited by 174
“Specifcally, studies have designed chatbots for eliciting self-disclosure [40, 41, 55] or increasing self-compassion by taking care of chatbots that experience distress [30, 38].”
BackgroundWhen the Social Becomes Non-Human: Young People's Perception of Social Support in Chatbots
Bae Brandtzæg, P. B., Skjuve, M., Kristoffer Dysthe, K. K., & Følstad, A. (2021) · Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3411764.3445318 · Cited by 153
“A recent study found that chatbots which provided self-disclosure had a reciprocal efect, promoting deeper participant self-disclosure [64].”
BackgroundFinding Love in Algorithms: Deciphering the Emotional Contexts of Close Encounters with AI Chatbots
Li, H., & Zhang, R. (2024) · doi:10.31219/osf.io/xd4k7 · Cited by 150
Park, G., Chung, J., & Lee, S. (2022) · Current Psychology · doi:10.1007/s12144-022-03932-z · Cited by 166
“Extant research has found a positive effect of emotional disclosure on perceived intimacy with a conversational partner (Carpenter & Greene, 2016; Ho et al., 2018; Lee et al., 2020), which then leads to several positive outcomes such as lower depression (Reis & Franks, 1994), and higher social support satisfaction (Jo…”
BackgroundInfluentialThird-party evaluators perceive AI as more compassionate than expert humans
Ovsyannikova, D., de Mello, V. O., & Inzlicht, M. (2025) · Communications Psychology · doi:10.1038/s44271-024-00182-6 · Cited by 159
Influence of Rapport and Social Presence with an AI Psychotherapy Chatbot on Users’ Self-Disclosure
Lee, J., Lee, D., & Lee, J.-G. (2022) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2022.2146227 · Cited by 130
“Furthermore, when people perceive a consciousness behind the chatbot they are using, they are likely to feel as if they are together, and such a feeling of social presence affects the extent to which they feel close to the chatbot (Y. C. Lee et al., 2020).”
BackgroundClosing the accessibility gap to mental health treatment with a personalized self-referral chatbot
Habicht, J., Viswanathan, S., Carrington, B., Hauser, T. U., Harper, R., & Rollwage, M. (2024) · Nature Medicine · doi:10.1038/s41591-023-02766-x · Cited by 132
“Moreover, the opportunity to tailor the questioning (based on AI) towards symptoms that are especially relevant to the patient’s problems allows them to explore their mental health problems in detail 38,39 and realize their need for help while reducing stigma 40 .”
Zhang, R., Li, H., Meng, H., Zhan, J., Gan, H., & Lee, Y.-C. (2025) · Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3713429 · Cited by 123
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Self-citationMindfulDiary: Harnessing Large Language Model to Support Psychiatric Patients' Journaling
Kim, T., Bae, S., Kim, H. A., Lee, S. H., Hong, H., Yang, C.-M., & Kim, Y. (2024) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642937 · Cited by 173
“Drawing on these findings, we discuss the implications of leveraging LLMs in the mental health domain, bridging the technical feasibility and their integration into clinical settings.”
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Curtis, R., Bartel, B., Ferguson, T., Blake, H. T., Northcott, C., Virgara, R., & Maher, C. A. (2021) · Journal of Medical Internet Research · doi:10.2196/31737 · Cited by 135
“Results were similar whether the autobiographical information was framed as being about the virtual assistant’s experience as a computer agent [44] or included human experiences that could not actually be true [29,47].”
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Zheng, Q., Tang, Y., Liu, Y., Liu, W., & Huang, Y. (2022) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3491102.3501855 · Cited by 139
“, [33, 78, 93, 94, 137], perceived CA collecting metrics regarding user self-reported personal experience characteristics such as capability in handling requests [52], personresponses.”
BackgroundSelf-citationTowards User-Centric Guidelines for Chatbot Conversational Design
Silva, G. R. S., & Canedo, E. D. (2022) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2022.2118244 · Cited by 111
“For example, small talk is a practice of talking about casual and out-of-domain subjects (De Cicco et al., 2021; Lee, Yamashita, Huang, & Fu, 2020), such as greetings, jokes, and the chatbot’s fictional background.”
BackgroundMethodCan Generative AI Chatbots Emulate Human Connection? A Relationship Science Perspective
Smith, M. G., Bradbury, T. N., & Karney, B. R. (2025) · Perspectives on Psychological Science · doi:10.1177/17456916251351306 · Cited by 88
“…a chatbot’s level of reciprocal self-disclosure (none, low, or high), disclosures from the chatbot encouraged further disclosure from the human participants and improved perceptions of intimacy with the chatbot (Lee et al., 2020), consistent with the predictions of the intimacy process model.”
Kang, E., & Kang, Y. (2023) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2022.2163775 · Cited by 87
“The concept of self-disclosure is defined as the behavior of sharing private personal information with others (Altman & Taylor, 1973; Lee et al., 2020).”
BackgroundModerator Chatbot for Deliberative Discussion
Kim, S., Eun, J., Seering, J., & Lee, J. (2021) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3449161 · Cited by 111
“The effectiveness of dyadic chatbots has mainly been assessed by manipulating message-level variables such as conversational style [42], empathic responses [33], typeface [8], and self-disclosure [48].”
BackgroundTell me more! assessing interactions with social robots from speech
Laban, G., George, J.-N., Morrison, V., & Cross, E. S. (2020) · Paladyn, Journal of Behavioral Robotics · doi:10.1515/pjbr-2021-0011 · Cited by 81
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“P6 similarly felt that LTM-triggered questions were repetitive, wishing that those questions were delivered in different forms periodically: “The only health issue that I have now is leg pain, so I can’t complain about the fact that it asks the same question every week.”
BackgroundResultInfluentialScholich, T., Barr, M., Wiltsey Stirman, S., & Raj, S. (2025) · JMIR Mental Health · doi:10.2196/69709 · Cited by 72
“In addition, LLMs can help identify patients who are at high risk based on data collected at intake and support therapists in promoting self-disclosure [9,10].”
Strategies for Fostering a Genuine Feeling of Connection in Technologically Mediated Systems
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“However, a reciprocal process when both parties self-disclose can better support intimacy by engaging both components of selfdisclosure (exposure and learning something personal about another) [97, 100] and by providing genuine responses that produce a positive feedback loop.”
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“To verify the long-term use effects of the proposed system, a longitudinal study is needed in future work [20].”
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Schick, A., Feine, J., Morana, S., Maedche, A., & Reininghaus, U. (2022) · JMIR mhealth and uhealth · doi:10.2196/28082 · Cited by 71
“A promising approach may be to enable reciprocal self-disclosure, in which the chatbot reveals sensitive information, as this has been shown to result in a reciprocal effect on promoting individuals’ self-disclosure [70], as well as perceived intimacy and enjoyment [74].”
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Xiao, Z., Liao, Q. V., Zhou, M., Grandison, T., & Li, Y. (2023) · Proceedings of the 28th International Conference on Intelligent User Interfaces · doi:10.1145/3581641.3584031 · Cited by 59
Papneja, H., & Yadav, N. (2024) · Personal and Ubiquitous Computing · doi:10.1007/s00779-024-01823-7 · Cited by 73
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Inform the Uninformed: Improving Online Informed Consent Reading with an AI-Powered Chatbot
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“Lee et al. built chatbots to practice journaling in the context of mental health research [53].”
Exploring people's perceptions of LLM-generated advice
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“Lee, Yamashita, Huang, and Fu (2020) developed a process consisting of three encounters with AI chatbots that progressively encouraged users to engage in self-disclosure (Figure 2), showing that AI self-disclosure effectively promotes longer responses and encourages users to express deeper thoughts…”
BackgroundResultPerceived Empathy of Technology Scale (PETS): Measuring Empathy of Systems Toward the User
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Strömel, K. R., Henry, S., Johansson, T., Niess, J., & Woźniak, P. W. (2024) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642032 · Cited by 45
van Straten, C. L., Peter, J., Kühne, R., & Barco, À. (2021) · Computers in Human Behavior · doi:10.1016/j.chb.2021.107135 · Cited by 46
Xygkou, A., Siriaraya, P., She, W. J., Covaci, A., & Ang, C. S. (2024) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2023.2292880 · Cited by 50
“…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 55
“[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 61
“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
“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
“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
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“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 52
Zarouali, B., Araujo, T., Ohme, J., & de Vreese, C. H. (2023) · Communication Methods and Measures · doi:10.1080/19312458.2022.2156489 · Cited by 38
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 42
“[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
“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 42
“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 36
“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
“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
“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
Influence of agent’s self-disclosure on human empathy
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“[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 39
“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
Designing Reenacted Chatbots to Enhance Museum Experience
Noh, Y.-G., & Hong, J.-H. (2021) · Applied Sciences · doi:10.3390/app11167420 · Cited by 40
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
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
“…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 33
“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 46
“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 57
“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
Potdevin, D., Clavel, C., & Sabouret, N. (2021) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2021.102612 · Cited by 28
Mai, V., Neef, C., & Richert, A. (2022) · Coaching | Theorie & Praxis · doi:10.1365/s40896-021-00063-3 · Cited by 33
Lee, Y., Yamashita, N., & Huang, Y. (2021) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3449196 · Cited by 29
“[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
“…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 31
Meyer, S., & Elsweiler, D. (2025) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2025.103514 · Cited by 39
Wang, Q., Jing, S., & Goel, A. K. (2022) · Designing Interactive Systems Conference · doi:10.1145/3532106.3533534 · Cited by 35
“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
“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) · ACM Conference on Conversational User Interfaces (CUI) · doi:10.1145/3543829.3543832 · Cited by 29
“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 55
“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
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 34
“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
“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 76
Self-citationGambino, A., & Liu, B. (2022) · Human-Machine Communication · doi:10.30658/hmc.4.6 · Cited by 25
“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 30
Zhang, R., Li, H., Chen, A., Liu, Z., & Lee, Y.-C. (2024) · Social Media + Society · doi:10.1177/20563051241290845 · Cited by 23
“…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) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3580995 · Cited by 33
“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
“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
“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
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 25
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 25
“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 24
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 24
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 25
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
“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
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 23
Metadata
- 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
- 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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