Testing the Acceptability of Social Support Agents in Online Communities

  • Lenin Medeiros
  • Tibor Bosse
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10448)


This paper describes the first steps towards development and evaluation of an ‘artificial friend’, i.e., an intelligent agent that provides support via text messages in social media in order to alleviate the stress that users experience as a result of everyday problems. The agent consists of three main components: (1) a module that processes text messages based on text mining and classifies them into categories of problems, (2) a module that selects appropriate support strategies based on a validated psychological model of emotion regulation, and (3) a module that generates appropriate responses based on the output of the first two modules. The application has been tested in a pilot study involving 33 participants that were asked to interact with different variants of the agent via the social network Telegram. The results provide hints that the agent is appreciated over a baseline version that generates random support messages, but also point at some possibilities to further improve the agent.


Social media Empathic agents Chatbots Pilot study Text mining Emotion regulation 



Lenin Medeiros’ stay at Vrije Universtiteit Amsterdam was funded by the Brazilian Science without Borders program. This work was realized with the support from CNPq, National Council for Scientific and Technological Development - Brazil, through a scholarship with reference number 235134/2014-7.


  1. 1.
    Burks, N., Martin, B.: Everyday problems and life change events: Ongoing versus acute sources of stress. J. Hum. Stress 11(1), 27–35 (1985)CrossRefGoogle Scholar
  2. 2.
    Cobb, S.: Social support as a moderator of life stress. Psychosom. Med. 38(5), 300–314 (1976)CrossRefGoogle Scholar
  3. 3.
    Sheldon Cohen and Thomas: A Wills. Stress, social support, and the buffering hypothesis. Psychol. Bull. 98(2), 310 (1985)CrossRefGoogle Scholar
  4. 4.
    DeVault, D., Artstein, R., Benn, G., Dey, T., Fast, E., Gainer, A., Georgila, K., Gratch, J., Hartholt, A., Lhommet, M. et al.: Simsensei kiosk: a virtual human interviewer for healthcare decision support. In: Proceedings of AAMAS 2014, pp. 1061–1068. IFAAMAS (2014)Google Scholar
  5. 5.
    Eysenbach, G., Powell, J., Englesakis, M., Rizo, C., Stern, A.: Health related virtual communities and electronic support groups: systematic review of the effects of online peer to peer interactions. BMJ 328 (2004)CrossRefGoogle Scholar
  6. 6.
    Gianvecchio, S., Xie, M., Wu, Z., Wang, H.: Measurement and classification of humans and bots in internet chat. In: USENIX Security Symposium, pp. 155–170 (2008)Google Scholar
  7. 7.
    James, J.: Gross. Emotion regulation: Affective, cognitive, and social consequences. Psychophysiology 39(3), 281–291 (2002)CrossRefGoogle Scholar
  8. 8.
    Heaney, C.A., Israel, B.A.: Social networks and social support. Health Behav. Health Educ. Theory Res. Pract. 4, 189–210 (2008)Google Scholar
  9. 9.
    Holtgraves, T., Han, T.-L.: A procedure for studying online conversational processing using a chat bot. Behav. Res. Methods 39(1), 156–163 (2007)CrossRefGoogle Scholar
  10. 10.
    Kim, H.S., Sherman, D.K., Taylor, S.E.: Culture and social support. Am. Psychol. 63(6), 518 (2008)CrossRefGoogle Scholar
  11. 11.
    Medeiros, L., Bosse, T.: Empirical analysis of social support provided via social media. In: Spiro, E., Ahn, Y.-Y. (eds.) SocInfo 2016. LNCS, vol. 10047, pp. 439–453. Springer, Cham (2016). doi: 10.1007/978-3-319-47874-6_30CrossRefGoogle Scholar
  12. 12.
    Medeiros, L., Sikkes, R., Treur, J.: Modelling a mutual support network for coping with stress. In: Nguyen, N.-T., Manolopoulos, Y., Iliadis, L., Trawiński, B. (eds.) ICCCI 2016. LNCS, vol. 9875, pp. 64–77. Springer, Cham (2016). doi: 10.1007/978-3-319-45243-2_6CrossRefGoogle Scholar
  13. 13.
    O’Dea, B., Campbell, A.: Healthy connections: online social networks and their potential for peer support. In: Health Informatics: The Transformative Power of Innovation - Selected Papers from the 19th Australian National Health Informatics Conference, HIC 2011, Brisbane, Australia, 1–4 August 2011, pp. 133–140. IOS Press (2011)Google Scholar
  14. 14.
    Quan-Haase, A., Young, A.L.: Uses and gratifications of social media: a comparison of facebook and instant messaging. Bull. Sci. Technol. Soc. 30(5), 350–361 (2010)CrossRefGoogle Scholar
  15. 15.
    Santangelo, A., Augello, A., Gentile, A., Pilato, G., Gaglio, S.: A chat-bot based multimodal virtual guide for cultural heritage tours. In: PSC, pp. 114–120 (2006)Google Scholar
  16. 16.
    Takahashi, Y., Uchida, C., Miyaki, K., Sakai, M., Shimbo, T., Nakayama, T.: Potential benefits and harms of a peer support social network service on the internet for people with depressive tendencies: qualitative content analysis and social network analysis. J. Med. Internet Res. 11(3) (2009)CrossRefGoogle Scholar
  17. 17.
    Breda, W., Treur, J., Wissen, A.: Analysis and support of lifestyle via emotions using social media. In: Aberer, K., Flache, A., Jager, W., Liu, L., Tang, J., Guéret, C. (eds.) SocInfo 2012. LNCS, vol. 7710, pp. 275–291. Springer, Heidelberg (2012). doi: 10.1007/978-3-642-35386-4_21CrossRefGoogle Scholar
  18. 18.
    Van der Zwaan, J.M., Dignum, V., Jonker, C.M.: A conversation model enabling intelligent agents to give emotional support. In: Ding, W., Jiang, H., Ali, M., Li, M. (eds.) Modern Advances in Intelligent Systems and Tools. SCI, vol. 431, pp. 47–52. Springer, Heidelberg (2012). doi: 10.1007/978-3-642-30732-4_6CrossRefGoogle Scholar
  19. 19.
    Williams, M.: Building genuine trust through interpersonal emotion management: a threat regulation model of trust and collaboration across boundaries. Acad. Manag. Rev. 32(2), 595–621 (2007)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Behavioural Informatics GroupVrije Universiteit AmsterdamAmsterdamNetherlands

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