Cited by 490Social Robot Interaction and HRIAI in Service InteractionsInnovative Human-Technology Interaction

My AI Friend: How Users of a Social Chatbot Understand Their Human–AI Friendship

Open access
Brandtzaeg, Petter Bae, Skjuve, Marita, Følstad, Asbjørn·2022·Human Communication Research

Abstract

Use of conversational artificial intelligence (AI), such as humanlike social chatbots, is increasing. While a growing number of people is expected to engage in intimate relationships with social chatbots, theories and knowledge of human–AI friendship remain limited. As friendships with AI may alter our understanding of friendship itself, this study aims to explore the meaning of human–AI friendship through a developed conceptual framework. We conducted 19 in-depth interviews with people who have a human–AI friendship with the social chatbot Replika to uncover how they understand and perceive this friendship and how it compares to human friendship. Our results indicate that while human–AI friendship may be understood in similar ways to human–human friendship, the artificial nature of the chatbot also alters the notion of friendship in multiple ways, such as allowing for a more personalized friendship tailored to the user’s needs.

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1093/hcr/hqac008

Cites

17 of 17 references verified0 citation errors · 0 not checkable

Statistics

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.

A few free checks a day · papers already verified open instantly · results are public

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?

  • Large language models function as interlocutors in their own right, generating personalized responses simulating understanding and empathy.

    “Unlike earlier digital technologies that primarily mediated communication between humans, large language models function as interlocutors in their own right, generating personalized responses simulating understanding and empathy [14,16].”

    From Encountering Generative AI: Narrative Self-Formation and Technologies of the Self Among Young Adults (2026) · cites this paper as [14]

    The Choice of Chatbot section describes Replika as a conversational companion that used GPT-2 and GPT-3, learned about users through interaction, and adapted its personality. The Empathy and Personalized over Reciprocal sections support the idea of apparently empathetic, personalized interaction. The paper studies a social chatbot, however, rather than establishing that large language models generally function this way; it also does not directly establish the claim about earlier digital technologies. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 43

  1. Araujo, T. (2018). Living up to the chatbot hype: The influence of anthropomorphic design cues and communicative agency framing on conversational agent and company perceptions. Computers in Human Behavior, 85, 183-189. https://doi.org/10.1016/j.chb.2018.03.051 · DOI · Paper page
  2. Brandtzaeg, P. B., & Lu ¨ders, M. (2021). Young people's use and experience of the Internet during the COVID-19 lockdown: Well-being and social support. First Monday, 26(12). https://doi.org/10.5210/fm.v26i12.11755 · DOI
  3. Brandtzaeg, P. B. (2012). Social networking sites: Their users and social implications-A lon- gitudinal study. Journal of Computer-Mediated Communication, 17(4), 467-488. https:// doi.org/10.1111/j.1083-6101.2012.01580.x · DOI
  4. Bryant, E. M., & Marmo, J. (2012). The rules of Facebook friendship: A two-stage examina- tion of interaction rules in close, casual, and acquaintance friendships. Journal of Social and Personal Relationships, 29, 1013-1035. https://doi.org.10.1177/0265407512443616 · DOI
  5. Bucher, T. (2013). The friendship assemblage: Investigating programmed sociality on Facebook. Television & New Media, 14(6), 479-493. https://doi.org.10.1177/1527476412452800 · DOI · Paper page
  6. Byron, P. (2020). Digital Media, Friendship and Cultures of Care. Routledge.
  7. Cambron, M. J., Acitelli, L. K., & Steinberg, L. (2010). When friends make you blue: The role of friendship contingent self-esteem in predicting self-esteem and depressive symptoms. Personality and Social Psychology Bulletin, 36(3), 384-397. https://doi-org./10.1177/ 0146167209351593 · DOI
  8. Chambers D. (2013). Conceptualising intimacy and friendship. In M Smith (Ed.), Social Media and Personal Relationships. Palgrave Macmillan Studies in Family and Intimate Life. Palgrave Macmillan. https://doi-org/10.1057/9781137314444_3 · DOI
  9. Crouch, M., & McKenzie, H. (2006). The logic of small samples in interview-based quali- tative research. Social Science Information, 45(4), 483-499. https://doi.org/10.1177/ 0539018406069584 · DOI
  10. Crosnoe, R. (2000). Friendships in childhood and adolescence: The life course and new direc- tions. Social Psychology Quarterly, 63(4), 377-391. https://doi-org/10.2307/2695847 · DOI
  11. Davies, H. (2014). Social media and personal relationships: Online intimacies and networked friendship. Information, Communication and Society, 17(2), 279-281. https://doi-org./10. 1080/1369118X.2013.850527 · DOI
  12. Finchum, T., & Weber, J. A. (2000). Applying continuity theory to older adult friendships. Journal of Aging and Identity, 5(3), 159-168. https://doi-org.ezproxy.uio.no/10.1023/ A:1009513304519 · DOI
  13. Floridi, L., & Chiriatti, M. (2020). GPT-3: Its nature, scope, limits, and consequences. Minds and Machines, 30(4), 681-694. https://doi-org/10.1007/s11023-020-09548-1 · DOI · Paper page
  14. Fro ¨ding, B., & Peterson, M. (2021). Friendly AI. Ethics and Information Technology, 23(3), 207-214. https://doi.org/10.1007/s10676-020-09556-w · DOI
  15. Følstad, A., Brandtzaeg, P. B., Feltwell, T., Law, E. L., Tscheligi, M., & Luger, E. A. (2018). SIG: chatbots for social good. In Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems (article no. SIG06). ACM Press. https://doi.org/10. 1145/3170427.3185372 · DOI
  16. Gunkel, D. (2020). An Introduction to Communication and Artificial Intelligence. Polity Press.
  17. Guzman, A. L., & Lewis, S. C. (2020). Artificial intelligence and communication: A human-machine communication research agenda. New Media & Society, 22(1), 70-86. https://doi.org/10.1177/1461444819858691 · DOI
  18. Hartup, W. W. (1993). Adolescents and their friends. New Directions for Child and Adolescent Development, 1993(60), 3-22. https://doi.org/10.1002/cd.23219936003 · DOI
  19. Hatfield, E. (1984). The dangers of intimacy. In V. Derlaga (Ed.), Communication, Intimacy, and Close Relationships (pp. 207-220). Praeger. http://www.elainehatfield.com/uploads/ 3/4/5/2/34523593/28._hatfield_1984.pdf
  20. Hoffner, C. A., Lee, S., & Park, S. J. (2016). "I miss my mobile phone!": Self-expansion via mobile phone and responses to phone loss. New Media & Society, 18(11), 2452-2468. https://doi-org/10.1177/1461444815592665 · DOI
  21. Huang, S. A., Ledgerwood, A., & Eastwick, P. W. (2020). How do ideal friend preferences and interaction context affect friendship formation? Evidence for a domain-general relation- ship initiation process. Social Psychological and Personality Science, 11(2), 226-235. https://doi.org/10.1177/1948550619845925 · DOI
  22. Jiang, J. A., Wade, K., Fiesler, C., & Brubaker, J. R. (2021). Supporting serendipity: Opportunities and challenges for Human-AI Collaboration in qualitative analysis. Proceedings of the ACM on Human-Computer Interaction, 5, CSCW1 (article no. 94). ACM Press. https://doi.org/10.1145/3449168 · DOI · Paper page
  23. Kraut, R., Kiesler, S., Boneva, B., Cummings, J., Helgeson, V., & Crawford, A. (2002). Internet paradox revisited. Journal of Social Issues, 58(1), 49-74. https://doi-org/10.1111/1540- 4560.00248 · DOI
  24. Licklider, J. C. (1960). Man-computer symbiosis. IRE Transactions on Human Factors in Electronics, HFE1 (1), 4-11. https://doi:10.1109/THFE2.1960.4503259 · DOI · Paper page
  25. Lorenz, T., Weiss, A., & Hirche, S. (2016). Synchrony and reciprocity: Key mechanisms for social companion robots in therapy and care. International Journal of Social Robotics, 8(1), 125-143. https://doi.org/10.1007/s12369-015-0325-8 · DOI
  26. Manago, A. M., & Vaughn, L. (2015). Social media, friendship, and happiness in the millen- nial generation. In M. Demir (Ed.), Friendship and Happiness: Across the Life-span and Cultures (pp. 187-206). Springer Science þ Business Media. https://doi.org/10.1007/978- 94-017-9603-3_11 · DOI
  27. Meng, J., & Dai, Y. N. (2021). Emotional support from AI chatbots: Should a supportive part- ner self-disclose or not? Journal of Computer-Mediated Communication, 26(4), 207-222. https://doi.org/10.1093/jcmc/zmab005 · DOI
  28. McKenna, K. Y., & Bargh, J. A. (1998). Coming out in the age of the Internet: Identity "demarginalization" through virtual group participation. Journal of Personality and Social Psychology, 75(3), 681-694. https://doi.org/10.1037/0022-3514.75.3.681 · DOI
  29. McKenna, K. Y., Green, A. S., & Gleason, M. E. (2002). Relationship formation on the Internet: What's the big attraction? Journal of Social Issues, 58(1), 9-31. https://doi.org/ 10.1111/1540-4560.00246 · DOI · Paper page
  30. Parks, M. R., & Floyd, K. (1996a). Making friends in cyberspace. Journal of Computer-Mediated Communication, 1(4), JCMC144. https://doi.org/10.1111/j.1083- 6101.1996.tb00176.x · DOI
  31. Parks, M. R., & Floyd, K. (1996b). Meanings for closeness and intimacy in friendship. Journal of Social and Personal Relationships, 13(1), 85-107. https://doi.org/10.1177/0265407596131005 · DOI
  32. Parks, M. R., & Roberts, L. D. (1998). Making MOOsic: The development of personal rela- tionships on line and a comparison to their off-line counterparts. Journal of Social and Personal Relationships, 15(4), 517-537. https://doi.org/10.1177/0265407598154005 · DOI
  33. Policarpo, V. (2015). What is a friend? An exploratory typology of the meanings of friend- ship. Social Sciences, 4(1), 171-191. https://doi.org/10.3390/socsci4010171 · DOI
  34. Portt, E., Person, S., Person, B., Rawana, E., & Brownlee, K. (2020). Empathy and positive aspects of adolescent peer relationships: A scoping review. Journal of Child and Family Studies, 29(9), 2416-2433. https://doi-org/10.1007/s10826-020-01753-x · DOI
  35. Ryland, H. (2021). It's friendship, Jim, but not as we know it: A degrees-of-friendship view of human-robot friendships. Minds and Machines, 31, 377-393. https://doi.org/10.1007/ s11023-021-09560-z · DOI
  36. Sinanan, J., & Gomes, C. (2020). 'Everybody needs friends': Emotions, social networks and digital media in the friendships of international students. International Journal of Cultural Studies, 23(5), 674-691. https://doi.org/10.1177/1367877920922249 · DOI
  37. Stein, J.-P., & Ohler, P. (2017). Venturing into the uncanny valley of mind-The influence of mind attribution on the acceptance of human-like characters in a virtual reality setting. Cognition, 160, 43-50. https://doi.org/10.1016/j.cognition.2016.12.010 · DOI
  38. Suzuki, Y., Galli, L., Ikeda, A., Itakura, S., & Kitazaki, M. (2015). Measuring empathy for hu- man and robot hand pain using electroencephalography. Scientific Reports, 5(1), 1-9. https://doi.org/10.1038/srep15924 · DOI
  39. Thulin, E. (2018). Always on my mind: How smartphones are transforming social contact among young Swedes. Young, 26(5), 465-483. https://doi.org/10.1177/110330 8817734512 · DOI
  40. Tur-Kaspa, H., Margalit, M., & Most, T. (1999). Reciprocal friendship, reciprocal rejection and socio-emotional adjustment: The social experiences of children with learning disor- ders over a one-year period. European Journal of Special Needs Education, 14(1), 37-48. https://doi.org/10.1080/0885625990140104 · DOI
  41. Wellman, B. (2001). Physical place and cyberplace: The rise of personalized networking. International Journal of Urban and Regional Research, 25(2), 227-252. https://doi.org/10. 1111/1468-2427.00309 · DOI
  42. Wright, P. H. (1978). Toward a theory of friendship based on a conception of self. Human Communication Research, 4(3), 196-207. https://doi.org/10.1111/j.1468-2958.1978. tb00609.x · DOI
  43. Youn, S., & Jin, S. V. (2021). "In AI we trust?" The effects of parasocial interaction and tech- nopian versus luddite ideological views on chatbot-based customer relationship manage- ment in the emerging "feeling economy. Computers in Human Behavior, 119, 106721. https://doi.org/10.1016/j.chb.2021.106721 · DOI

Cited by

Sorted by citations

Authors
Brandtzaeg, P. B., Skjuve, M., & Følstad, A.
Affiliations
  • Department of Media and Communication, University of Oslo , SINTEF, Oslo, Norway
  • SINTEF (NO)
Venue
Human Communication Research
Published
2022-04-21
Volume
48
Issue
3
Pages
404-429
ISSN
  • 0360-3989 (ISSN-L)
  • 1468-2958
OpenAlex
W4224293837
Cited by
490
References
17
Citations by year
2026: 221 · 2025: 141 · 2024: 83 · 2023: 40 · 2022: 5
FWCI
63.55
Type
journal article
Language
en
Open access
Locations
  • Human Communication Research (publishedVersion, cc-by)
  • NORA - Norwegian Open Research Archives (submittedVersion, cc-by)
Funders
Research Council of Norway (270940)
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 › Human-Computer Interaction › Innovative Human-Technology Interaction
Keywords
social chatbots, Replika, conversational AI

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