Social Utilities and Personality Traits for Group Recommendation: A Pilot User Study

Silvia Rossi, Francesco Cervone

2016

Abstract

Recommendations to a group of users can be provided by the aggregation of individual users’ recommendations using social choice functions. Standard aggregation techniques do not consider the possibility of evaluating social interactions, roles, and influences among group’s members, as well as their personalities, which are, indeed, crucial factors in the group’s decision-making process. Instead of defining a specific social choice function to take into account such features, the proposed solution relies on the definition of a utility function, for each agent, that takes into account other group members’ preferences. Such function models the level of a user’s altruistic behavior starting from his/her agreeableness personality trait. Once such utility values are evaluated, the goal is to recommend items that maximize the social welfare. Performance is evaluated with a pilot user study and compared with respect to Least Misery. Results showed that while for small groups LM performs slightly better, in the other cases the two methods are comparable.

References

  1. Anderson, C., John, O. P., Keltner, D., and Kring, A. M. (2001). Who attains social status? effects of personality and physical attractiveness in social groups. Journal of personality and social psychology, 81(1):116.
  2. Brody, L. R. (2000). The socialization of gender differences in emotional expression: Display rules, infant temperament, and differentiation. Gender and emotion: Social psychological perspectives, pages 24-47.
  3. Charness, G. and Rabin, M. (2002). Understanding social preferences with simple tests. Quarterly journal of Economics, pages 817-869.
  4. Costa, P. T. and MacCrae, R. R. (1992). Revised NEO personality inventory (NEO PI-R) and NEO five-factor inventory (NEO FFI): Professional manual. Psychological Assessment Resources.
  5. Costa, P. T. and McCrae, R. R. (1995). Primary traits of eysenck's pen system: three-and vfie-factor solutions. Journal of personality and social psychology, 69(2):308.
  6. Donnellan, M. B., Oswald, F. L., Baird, B. M., and Lucas, R. E. (2006). The mini-ipip scales: tiny-yet-effective measures of the big vfie factors of personality. Psychological assessment, 18(2):192.
  7. Dooms, S., De Pessemier, T., and Martens, L. (2013). Movietweetings: a movie rating dataset collected from twitter. In Workshop on Crowdsourcing and Human Computation for Recommender Systems, CrowdRec at RecSys 2013.
  8. Dunn, G., Wiersema, J., Ham, J., and Aroyo, L. (2009). Evaluating interface variants on personality acquisition for recommender systems. In Houben, G.-J., McCalla, G., Pianesi, F., and Zancanaro, M., editors, User Modeling, Adaptation, and Personalization, volume 5535 of Lecture Notes in Computer Science, pages 259-270. Springer Berlin Heidelberg.
  9. Gartrell, M., Xing, X., Lv, Q., Beach, A., Han, R., Mishra, S., and Seada, K. (2010). Enhancing group recommendation by incorporating social relationship interactions. In Proc. of the 16th ACM International Conference on Supporting Group Work, pages 97-106. ACM.
  10. Goldberg, L. R. (1992). The development of markers for the big-vfie factor structure. Psychological assessment, 4(1):26.
  11. Gosling, S. D., Rentfrow, P. J., and Swann, W. B. (2003). A very brief measure of the big-vfie personality domains. Journal of Research in personality, 37(6):504- 528.
  12. Hu, R. and Pu, P. (2011). Enhancing collaborative filtering systems with personality information. In Proceedings of the Fifth ACM Conference on Recommender Systems, RecSys 7811, pages 197-204. ACM.
  13. Ma, Z. (2005). Exploring the relationships between the big vfie personality factors, conflict styles, and bargaining behaviors. In IACM 18th Annual Conference.
  14. Masthoff, J. (2011). Group recommender systems: Combining individual models. In Recommender Systems Handbook, pages 677-702.
  15. McCrae, R. R. and Costa, P. T. (1985). Updating norman's” adequacy taxonomy”: Intelligence and personality dimensions in natural language and in questionnaires. Journal of personality and social psychology, 49(3):710.
  16. McCrae, R. R. and Costa, P. T. (1987). Validation of the vfie-factor model of personality across instruments and observers. Journal of personality and social psychology, 52(1):81.
  17. McCrae, R. R. and Costa, P. T. (1989). The structure of interpersonal traits: Wiggins's circumplex and the vfiefactor model. Journal of personality and social psychology, 56(4):586.
  18. Nunes, M. A. S. and Hu, R. (2012). Personality-based recommender systems: An overview. In Proceedings of the Sixth ACM Conference on Recommender Systems, RecSys 7812, pages 5-6, New York, NY, USA. ACM.
  19. O'connor, M., Cosley, D., Konstan, J. A., and Riedl, J. (2001). Polylens: a recommender system for groups of users. In ECSCW 2001, pages 199-218. Springer.
  20. Quijano-Sanchez, L., Recio-Garcia, J. A., Diaz-Agudo, B., and Jimenez-Diaz, G. (2013). Social factors in group recommender systems. ACM Trans. Intell. Syst. Technol., 4(1):1-30.
  21. Rossi, S., Caso, A., and Barile, F. (2015). Combining users and items rankings for group decision support. In Trends in Practical Applications of Agents, MultiAgent Systems and Sustainability, volume 372 of Advances in Intelligent Systems and Computing, pages 151-158. Springer International Publishing.
  22. Sager, K. L. and Gastil, J. (2006). The origins and consequences of consensus decision making: A test of the social consensus model. Southern Communication Journal, 71(1):1-24.
  23. Salehi-Abari, A. and Boutilier, C. (2014). Empathetic social choice on social networks. In 13th International Conference on Autonomous Agents and Multiagent Systems, pages 693-700.
Download


Paper Citation


in Harvard Style

Rossi S. and Cervone F. (2016). Social Utilities and Personality Traits for Group Recommendation: A Pilot User Study . In Proceedings of the 8th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-758-172-4, pages 38-46. DOI: 10.5220/0005709600380046


in Bibtex Style

@conference{icaart16,
author={Silvia Rossi and Francesco Cervone},
title={Social Utilities and Personality Traits for Group Recommendation: A Pilot User Study},
booktitle={Proceedings of the 8th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2016},
pages={38-46},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005709600380046},
isbn={978-989-758-172-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 8th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - Social Utilities and Personality Traits for Group Recommendation: A Pilot User Study
SN - 978-989-758-172-4
AU - Rossi S.
AU - Cervone F.
PY - 2016
SP - 38
EP - 46
DO - 10.5220/0005709600380046