Skip to main content
SpringerLink
Log in

Beyond Item Recommendation: Using Recommendations to Stimulate Knowledge Sharing in Group Decisions

  • Conference paper
  • First Online:
Social Informatics (SocInfo 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10540))

Included in the following conference series:

Abstract

The intensity of domain knowledge exchange among group members is an important factor that directly influences group decision quality. The more frequent information is exchanged among group members, the higher the quality of the corresponding decision. In this paper we present results of an empirical study conducted with groups of students – the task of each group was to take a decision regarding the exam topics the group prefers. This group decision had to be taken on the basis of a group decision support environment with included recommendation functionality and a discussion forum that allows for information exchange among group members. Depending on the included variant of the group recommendation algorithm, groups received recommendations that varied in terms of recommendation diversity. The results of the study show that increased recommendation diversity leads to an increased degree of information exchange among group members.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Institutional subscriptions

Notes

  1. 1.

    The work presented in this paper has been conducted within the scope of the Horizon 2020 project OpenReq (Intelligent Recommendation & Decision Technologies for Community-Driven Requirements Engineering).

References

  1. Adomavicius, G., Bockstedt, J., Curley, S., Zhang, J.: Recommender systems, consumer preferences, and anchoring effects. In: Decisions@RecSys2011 Workshop, Chicago, IL, USA, pp. 35–42. ACM (2011)

    Google Scholar 

  2. Boratto, L., Carta, S.: The rating prediction task in a group recommender system that automatically detects groups: architectures, algorithms, and performance evaluation. J. Intell. Inf. Syst. (JIIS) 45(2), 221–245 (2015)

    Article  Google Scholar 

  3. Chen, L., deGemmis, M., Felfernig, A., Lops, P., Ricci, F., Semeraro, G.: Human decision making and recommender systems. ACM Trans. Interact. Intell. Syst. 3(3) (2013). Article no. 17

    Google Scholar 

  4. Chen, Y., Pu, P.: CoFeel: emotional social interface in group recommender systems. In: RecSys 2012 Workshop on Interfaces for Recommender Systems, Dublin, Ireland, pp. 48–55 (2012)

    Google Scholar 

  5. O’Connor, M., Cosley, D., Konstan, J., Riedl, J.: PolyLens: a recommmender system for groups of users. In: European Conference on Computer-Supported Cooperative Work, pp. 199–218. ACM (2001)

    Google Scholar 

  6. Felfernig, A., Zehentner, C., Ninaus, G., Grabner, H., Maalej, W., Pagano, D., Weninger, L., Reinfrank, F.: Group decision support for requirements negotiation. In: Ardissono, L., Kuflik, T. (eds.) UMAP 2011. LNCS, vol. 7138, pp. 105–116. Springer, Heidelberg (2012). doi:10.1007/978-3-642-28509-7_11

    Chapter  Google Scholar 

  7. Felfernig, A.: Biases in decision making. In: International Workshop on Decision Making and Recommender Systems 2014, pp. 32–37. CEUR Proceedings (2014)

    Google Scholar 

  8. Felfernig, A., Atas, M., Tran, T.N.T., Stettinger, M., Erdeniz, S.P., Leitner, G.: An analysis of group recommendation heuristics for high- and low-involvement items. In: Benferhat, S., Tabia, K., Ali, M. (eds.) IEA/AIE 2017. LNCS (LNAI), vol. 10350, pp. 335–344. Springer, Cham (2017). doi:10.1007/978-3-319-60042-0_39

    Chapter  Google Scholar 

  9. Felfernig, A., Stettinger, M., Leitner, G.: Fostering knowledge exchange using group recommendations. In: RecSys 2015 Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS 2015), Vienna, Austria (2015)

    Google Scholar 

  10. Ninaus, G., Felfernig, A., Stettinger, M., Reiterer, S., Leitner, G., Weninger, L., Schanil, W.: IntelliReq: intelligent techniques for software requirements engineering. In: European Conference on AI, Prestigious Applications of Intelligent Systems (PAIS) (2014)

    Google Scholar 

  11. Jameson, A., Willemsen, M.C., Felfernig, A., Gemmis, M., Lops, P., Semeraro, G., Chen, L.: Human decision making and recommender systems. In: Ricci, F., Rokach, L., Shapira, B. (eds.) Recommender Systems Handbook. LNCS (LNAI), pp. 611–648. Springer, Boston, MA (2015). doi:10.1007/978-1-4899-7637-6_18

    Chapter  Google Scholar 

  12. Jameson, A., Smyth, B.: Recommendation to groups. In: Brusilovsky, P., Kobsa, A., Nejdl, W. (eds.) The Adaptive Web. LNCS, vol. 4321, pp. 596–627. Springer, Heidelberg (2007). doi:10.1007/978-3-540-72079-9_20

    Chapter  Google Scholar 

  13. Jameson, A.: More than the sum of its members: challenges for group recommender systems. In: International Working Conference on Advanced Visual Interfaces, AVI 2004, Gallipoli (Lecce), Italy, pp. 48–54. ACM (2004)

    Google Scholar 

  14. Jannach, D., Zanker, M., Felfernig, A., Friedrich, G.: Recommender Systems: An Introduction. Cambridge University Press, New York (2010)

    Book  Google Scholar 

  15. Kudenko, D., Bauer, M., Dengler, D.: Group decision making through mediated discussions. In: Brusilovsky, P., Corbett, A., Rosis, F. (eds.) UM 2003. LNCS (LNAI), vol. 2702, pp. 238–247. Springer, Heidelberg (2003). doi:10.1007/3-540-44963-9_32

    Chapter  Google Scholar 

  16. Masthoff, J.: Group modeling: selecting a sequence of television items to suit a group of viewers. UMUAI 14(1), 37–85 (2004)

    Google Scholar 

  17. Masthoff, J., Gatt, A.: In pursuit of satisfaction and the prevention of embarrassment: affective state in group recommender systems. User Model. User-Adapted Interact. 16(3–4), 281–319 (2006). Springer

    Article  Google Scholar 

  18. Masthoff, J.: Group Recommender Systems: Combining Individual Models. Recommender Systems Handbook, pp. 677–702 (2011)

    Google Scholar 

  19. McCarthy, K., Salamo, M., Coyle, L., McGinty, L., Smyth, B., Nixon, P.: Group Recommender Systems: A Critiquing based Approach. In: IUI 2006, pp. 267–269. ACM (2006)

    Google Scholar 

  20. McGinty, L., Smyth, B.: On the role of diversity in conversational recommender systems. In: Ashley, K.D., Bridge, D.G. (eds.) ICCBR 2003. LNCS (LNAI), vol. 2689, pp. 276–290. Springer, Heidelberg (2003). doi:10.1007/3-540-45006-8_23

    Chapter  Google Scholar 

  21. Mojzisch, A., Schulz-Hardt, S.: Knowing other’s preferences degrades the quality of group decisions. J. Personal. Soc. Psychol. 98, 794–808 (2010)

    Article  Google Scholar 

  22. Ricci, F., Rokach, L., Shapira, B., Kantor, P.: Recommender Systems Handbook. Springer, New York (2011)

    Book  MATH  Google Scholar 

  23. Schulz-Hardt, S., Brodbeck, F., Mojzisch, A., Kerschreiter, R., Frey, D.: Group decision making in hidden profile situations: dissent as a facilitator of decision quality. J. Personal. Soc. Psychol. 91, 1080–1093 (2006)

    Article  Google Scholar 

  24. Stasser, G., Titus, W.: Pooling of unshared information in group decision making: biased information sharing during discussion. J. Personal. Soc. Psychol. 48, 1467–1478 (1985)

    Article  Google Scholar 

  25. Stettinger, M., Felfernig, A., Leitner, G., Reiterer, S., Jeran, M.: Counteracting serial position effects in the CHOICLA group decision support environment. In: 20th ACM Conference on Intelligent User Interfaces (IUI 2015), pp. 148–157 (2015)

    Google Scholar 

  26. Stettinger, M., Felfernig, A., Leitner, G., Reiterer, S.: Counteracting anchoring effects in group decision making. In: Ricci, F., Bontcheva, K., Conlan, O., Lawless, S. (eds.) UMAP 2015. LNCS, vol. 9146, pp. 118–130. Springer, Cham (2015). doi:10.1007/978-3-319-20267-9_10

    Chapter  Google Scholar 

  27. Wittenbaum, G., Hollingshead, A., Botero, I.: From cooperative to motivated information sharing in groups: moving beyond the hidden profile paradigm. In: Communication Monographs, pp. 286–310 (2004)

    Google Scholar 

  28. Yaniv, I.: Group diversity and decision quality: amplification and attenuation of the framing effect. Int. J. Forecast. 27, 41–49 (2011)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute of Software Technology, Graz University of Technology, Inffeldgasse 16b/II, 8010, Graz, Austria

    Müslüm Atas, Alexander Felfernig, Martin Stettinger & Thi Ngoc Trang Tran

Authors
  1. Müslüm Atas
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Alexander Felfernig
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Martin Stettinger
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Thi Ngoc Trang Tran
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Müslüm Atas .

Editor information

Editors and Affiliations

  1. Indiana University, Bloomington, Indiana, USA

    Giovanni Luca Ciampaglia

  2. University of Washington, Seattle, Washington, USA

    Afra Mashhadi

  3. University of Oxford, Oxford, United Kingdom

    Taha Yasseri

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Atas, M., Felfernig, A., Stettinger, M., Tran, T.N.T. (2017). Beyond Item Recommendation: Using Recommendations to Stimulate Knowledge Sharing in Group Decisions. In: Ciampaglia, G., Mashhadi, A., Yasseri, T. (eds) Social Informatics. SocInfo 2017. Lecture Notes in Computer Science(), vol 10540. Springer, Cham. https://doi.org/10.1007/978-3-319-67256-4_29

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-67256-4_29

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67255-7

  • Online ISBN: 978-3-319-67256-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation