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An Empirical Investigation of Similarity-Driven Trust Dynamics in a Social Network
DOI
Open Access
Description
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.
