The DOI matches its Crossref record; 132 of the 136 references it cites were found in a registry or an index.
Effectiveness of an Empathic Chatbot in Combating Adverse Effects of Social Exclusion on Mood
Open accessAbstract
From past research it is well known that social exclusion has detrimental consequences for mental health. To deal with these adverse effects, socially excluded individuals frequently turn to other humans for emotional support. While chatbots can elicit social and emotional responses on the part of the human interlocutor, their effectiveness in the context of social exclusion has not been investigated. In the present study, we examined whether an empathic chatbot can serve as a buffer against the adverse effects of social ostracism. After experiencing exclusion on social media, participants were randomly assigned to either talk with an empathetic chatbot about it (e.g., "I'm sorry that this happened to you") or a control condition where their responses were merely acknowledged (e.g., "Thank you for your feedback"). Replicating previous research, results revealed that experiences of social exclusion dampened the mood of participants. Interacting with an empathetic chatbot, however, appeared to have a mitigating impact. In particular, participants in the chatbot intervention condition reported higher mood than those in the control condition. Theoretical, methodological, and practical implications, as well as directions for future research are discussed.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source says what the claim attributes to it.
In the citing paper
“Relative to chatbots that do not express empathy, chatbots that express empathy lead to more favorable ratings of companionship, i.e., the activities done together are perceived as more enjoyable or exciting (Boucher et al. 2021; Leite et al. 2013), and better mood after experiencing social exclusion (De Gennaro, Krumhuber, and Lucas 2020).”
From AI Companions Reduce Loneliness (2024) · cites this paper as De Gennaro, Krumhuber, and Lucas 2020
In the citing paper
“CAs with advanced empathetic skills have improved user affinities and experiences [77,78].”
From Conversational Agent Interventions for Mental Health Problems: Systematic Review and Meta-analysis of Randomized Controlled Trials (2023) · cites this paper as [77]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Faul, F., Erdfelder, E., Lang, A.-G., & Buchner, A. (2007) · Behavior Research Methods · doi:10.3758/bf03193146 · Cited by 65,971
Tversky, A., & Kahneman, D. (1974) · Science · doi:10.1126/science.185.4157.1124 · Cited by 28,810
The need to belong: Desire for interpersonal attachments as a fundamental human motivation.
Baumeister, R. F., & Leary, M. R. (1995) · Psychological Bulletin · doi:10.1037//0033-2909.117.3.497 · Cited by 23,245
Judgment under Uncertainty: Heuristics and Biases
Tversky, A., & Kahneman, D. (1975) · Utility, Probability, and Human Decision Making · doi:10.1007/978-94-010-1834-0_8 · Cited by 22,650
PSYCHOLOGICAL CONDITIONS OF PERSONAL ENGAGEMENT AND DISENGAGEMENT AT WORK.
Kahn, W. A. (1990) · Academy of Management Journal · doi:10.2307/256287 · Cited by 10,975
Picard, R. W. (1997) · MIT Press · doi:10.7551/mitpress/1140.001.0001 · Cited by 7,382
(1997) · Choice Reviews Online · doi:10.5860/choice.34-3702 · Cited by 4,872
Harnad, S. (1990) · Physica D: Nonlinear Phenomena · doi:10.1016/0167-2789(90)90087-6 · Cited by 4,235 · cited 1×
“Also, such errors have been shown to reduce trust and acceptance of agents (Blascovich and McCall, 2013; Wang et al., 2013; Lucas et al., 2018a), with chatbots attempting to use an entirely natural language interface being prone for failure (Luger and Sellen, 2016; see also Harnad, 1990).”
BackgroundOn seeing human: A three-factor theory of anthropomorphism
Epley, N., Waytz, A., & Cacioppo, J. T. (2007) · Psychological Review · doi:10.1037/0033-295x.114.4.864 · Cited by 4,069
Machines and Mindlessness: Social Responses to Computers
Nass, C., & Moon, Y. (2000) · Journal of Social Issues · doi:10.1111/0022-4537.00153 · Cited by 4,022 · cited 1×
“Moreover, people often rely on heuristics or cognitive shortcuts (Tversky and Kahneman, 1974) and mindlessly apply social scripts from human-human interaction when interacting with computers (Sundar and Nass, 2000).”
Background
Flagged first, then by citations
4 of the 136 references couldn’t be matched to a known paper.
Research works printed but not linked: 13
- Bales, 1966, Size of group as a factor in the interaction profile, Small Groups: Studies in Social Interaction, 495
- Burri, 2018, Improving User Trust Towards Conversational Chatbot Interfaces With Voice Output (Dissertation).
- DeVault, 2014, SimInterviewer: a virtual human interviewer for healthcare decision support, Proceedings of the 13th Conference on Autonomous Agents and Multi-Agent Systems
- Dunbar, 1998, Grooming, Gossip, and the Evolution of Language.
- 2019, General Best Practices - Messenger Platform.
- Faulkner, 1997, The “silent treatment”: Its incidence and impact, Proceedings of the 69th Annual Midwestern Psychological Association
- Gardner, 2005, Social Snacking and Shielding: Using social symbols, selves, and surrogates in the service of belonging needs, The Social Outcast: Ostracism, Social Exclusion, Rejection, and Bullying
- Lim, 2017, Predicting Outcomes in Online Chatbot-Mediated Therapy.
- Lucas, 2010, Wanting connection, fearing rejection: the paradox of loneliness., Human, 17, 37
- Lucas, Getting to know each other: the role of social dialogue in recovery from errors in social robots, Proceedings of the Conference on Human-Robot Interaction
- Pickett, 2005, The social monitoring system: enhanced sensitivity to social cues as an adaptive response to social exclusion, The social Outcast: Ostracism, Social Exclusion, Rejection, and Bullying, 213
- Williams, 2005, The Social Outcast.
- Zumstein, 2017, Chatbots: an interactive technology for personalized communication, transactions and services., IADIS Int. J. Internet, 15, 96
Cited by
Sorted by citations
Huang, W., Hew, K. F., & Fryer, L. K. (2022) · Journal of Computer Assisted Learning · doi:10.1111/jcal.12610 · Cited by 830
Artificially intelligent chatbots in digital mental health interventions: a review
Boucher, E. M., Harake, N. R., Ward, H. E., Stoeckl, S. E., Vargas, J., Minkel, J., Parks, A. C., & Zilca, R. (2021) · Expert Review of Medical Devices · doi:10.1080/17434440.2021.2013200 · Cited by 440
Mariani, M. M., Hashemi, N., & Wirtz, J. (2023) · Journal of Business Research · doi:10.1016/j.jbusres.2023.113838 · Cited by 421
Perceptions and opinions of patients about mental health chatbots: scoping review
Abd-Alrazaq, A. A., Alajlani, M., Ali, N., Denecke, K., Bewick, B. M., & Househ, M. (2021) · Journal of Medical Internet Research · doi:10.2196/17828 · Cited by 301
Zhai, C., & Wibowo, S. (2023) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2023.100134 · Cited by 425
Metadata
- Authors
- de Gennaro, M., Krumhuber, E. G., & Lucas, G.
- Affiliations
- University College London (GB)
- University of Southern California (US)
- Corresponding author
- Krumhuber, Eva G.
- Venue
- Frontiers in Psychology
- Publisher
- Frontiers Media SA
- Published
- 2020-01-23
- Volume
- 10
- Pages
- 3061-3061
- ISSN
- 1664-1078 (ISSN-L)
- PMC
- PMC6989433
- OpenAlex
- W3000840260
- Cited by
- 265
- References
- 136
- Citations by year
- 2026: 39 · 2025: 63 · 2024: 69 · 2023: 29 · 2022: 37 · 2021: 26 · 2020: 2
- FWCI
- 25.69
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Frontiers in Psychology (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- UCL Discovery (University College London) (submittedVersion)
- Topics
- Social Sciences › Psychology › Social Psychology › Death Anxiety and Social Exclusion
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Keywords
- social exclusion, ostracism, mood, chatbot intervention, emotional support, buffer hypothesis, mental health
About these checks
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.
Statistics and arithmetic are recomputed, not judged.
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 ›
Are you an author, or do you see a problem with this page? Request a review