How much trust a user places in a recommender is crucial to the uptake of the recommendations. Although prior work established various factors that build and sustain user trust, their comparative impact has not been studied in depth. This paper presents the results of a crowdsourced study examining the impact of various recommendation interfaces and content selection strategies on user trust. It evaluates the subjective ranking of nine key factors of trust grouped into three dimensions and examines the differences observed with respect to users' personality traits.
%0 Conference Paper
%1 citeulike:14311450
%A Berkovsky, Shlomo
%A Taib, Ronnie
%A Conway, Dan
%B Proceedings of the 22Nd International Conference on Intelligent User Interfaces
%C New York, NY, USA
%D 2017
%I ACM
%K iui2017, recommender, trust
%P 287--300
%R 10.1145/3025171.3025209
%T How to Recommend?: User Trust Factors in Movie Recommender Systems
%U http://dx.doi.org/10.1145/3025171.3025209
%X How much trust a user places in a recommender is crucial to the uptake of the recommendations. Although prior work established various factors that build and sustain user trust, their comparative impact has not been studied in depth. This paper presents the results of a crowdsourced study examining the impact of various recommendation interfaces and content selection strategies on user trust. It evaluates the subjective ranking of nine key factors of trust grouped into three dimensions and examines the differences observed with respect to users' personality traits.
%@ 978-1-4503-4348-0
@inproceedings{citeulike:14311450,
abstract = {{How much trust a user places in a recommender is crucial to the uptake of the recommendations. Although prior work established various factors that build and sustain user trust, their comparative impact has not been studied in depth. This paper presents the results of a crowdsourced study examining the impact of various recommendation interfaces and content selection strategies on user trust. It evaluates the subjective ranking of nine key factors of trust grouped into three dimensions and examines the differences observed with respect to users' personality traits.}},
added-at = {2017-11-15T17:02:25.000+0100},
address = {New York, NY, USA},
author = {Berkovsky, Shlomo and Taib, Ronnie and Conway, Dan},
biburl = {https://www.bibsonomy.org/bibtex/29b8b18cbe608cd6f6dd3bd9cb93c48bb/brusilovsky},
booktitle = {Proceedings of the 22Nd International Conference on Intelligent User Interfaces},
citeulike-article-id = {14311450},
citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=3025209},
citeulike-linkout-1 = {http://dx.doi.org/10.1145/3025171.3025209},
doi = {10.1145/3025171.3025209},
interhash = {937acfcda5412e09914a070292a14144},
intrahash = {9b8b18cbe608cd6f6dd3bd9cb93c48bb},
isbn = {978-1-4503-4348-0},
keywords = {iui2017, recommender, trust},
location = {Limassol, Cyprus},
pages = {287--300},
posted-at = {2017-03-15 12:22:37},
priority = {0},
publisher = {ACM},
series = {IUI '17},
timestamp = {2017-11-15T17:02:25.000+0100},
title = {{How to Recommend?: User Trust Factors in Movie Recommender Systems}},
url = {http://dx.doi.org/10.1145/3025171.3025209},
year = 2017
}