@inproceedings{7cf2fa12e20e4f6398e73f6518e3fa51,
title = "Dynamics of human trust in recommender systems",
abstract = "The trust that humans place on recommendations is key to the success of recommender systems. The formation and decay of trust in recommendations is a dynamic process influenced by context, human preferences, accuracy of recommendations, and the interactions of these factors. This paper describes two psychological experiments (N=400) that evaluate the evolution of trust in recommendations over time, under personalized and nonpersonalized recommendations by matching or not matching a participant's profile. Main findings include: Humans trust inaccurate recommendations more than they should; when recommendations are personalized, they lose trust in inaccurate recommendations faster than when recommendations are not personalized; and participants report less trust and lower overall ratings of personalized but inaccurate recommendations compared to not-personalized inaccurate recommendations. We make connections to the possible implications of these psychological findings to the design of recommender systems.",
keywords = "Cognitive processes, Decision making, Trust",
author = "Harman, {Jason L.} and John O'Donovan and Tarek Abdelzaher and Cleotilde Gonzalez",
note = "Publisher Copyright: Copyright {\textcopyright} 2014 ACM.; 8th ACM Conference on Recommender Systems, RecSys 2014 ; Conference date: 06-10-2014 Through 10-10-2014",
year = "2014",
month = oct,
day = "6",
doi = "10.1145/2645710.2645761",
language = "English (US)",
series = "RecSys 2014 - Proceedings of the 8th ACM Conference on Recommender Systems",
publisher = "Association for Computing Machinery",
pages = "305--308",
booktitle = "RecSys 2014 - Proceedings of the 8th ACM Conference on Recommender Systems",
address = "United States",
}