Abstract
Presently, people often create and keep lists of other people with similar preferences for hobbies, such as books, movies, music, and food in online social network service systems. Recent studies in recommender systems have shown that the user’s data can be used to recommend items based on other users’ preferences (e.g. as implemented in amazon.com). To make such systems more effective, there is a need to understand the mechanism of human trust formation. The goal of this study is to develop cognitive models describing the trust formation in social networks. This paper presents results of a controlled experiment conducted to collect human behavior data through a series of trust evaluation tasks.
Chapter PDF
Similar content being viewed by others
Keywords
References
Byrne, D.: The attraction paradigm. Academic Press, New York (1971)
Sinha, R., Swearingen, K.: Comparing recommendations made by online systems and friends. In: Proceedings of the DELOS-NSF Workshop on Personalization and Recommender Systems in Digital Libraries. Dublin, Ireland (2001)
Golbeck, J.: Trust and Nuanced Profile Similarity in Online Social Networks. ACM Transactions on the Web 3(4-12), 1–32 (2009)
Walter, E.F., Battiston, S., Schweitzer, F.: A model of a trust-based recommendation system on a social network. Journal of Autonomous Agents and Multi-Agent Systems 16(1), 57–74 (2007)
Ziegler, C.N., Lausen, G.: Spreading activation models for trust propagation. In: Proceedings of the IEEE International Conference on e-Technology, e-Commerce, and e-Service, pp. 83–97. IEEE Computer Society Press, Los Alamitos (2004)
Ziegler, C.N., Golbeck, J.: Investigating Correlations of Trust and Interest Similarity. Decision Support Systems 42(2), 460–475 (2006)
Hayashi, Y.: The effect of "Maverick": A study of Group Dynamics on Breakthrough in Collaborative Problem solving. In: Proceedings of the 34th Annual Conference of the Cognitive Science Society, pp. 444–449. Lawrence Erlbaum Associates, Hillsdale (2012)
Joinson, A.N.: Understanding the psychology of internet behavior: virtual worlds, real lives. Palgrave, Basingstoke (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Hayashi, Y., Kryssanov, V., Ogawa, H. (2013). An Empirical Investigation of Similarity-Driven Trust Dynamics in a Social Network. In: Kurosu, M. (eds) Human-Computer Interaction. Users and Contexts of Use. HCI 2013. Lecture Notes in Computer Science, vol 8006. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39265-8_3
Download citation
DOI: https://doi.org/10.1007/978-3-642-39265-8_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-39264-1
Online ISBN: 978-3-642-39265-8
eBook Packages: Computer ScienceComputer Science (R0)