Abstract: Interpersonal trust is widely cited as an important component in several network systems such as peer-to-peer networks, e-commerce, and semantic web. However, there has been less research on measuring interpersonal trust due to the difficulty of collecting data that accurately reflect interpersonal trust. Currently, friends of a user in almost all OSNs are indistinguishable, that is, there is no explicit indication of the strength of trust between a user and his/her close friends, as opposed to acquaintances. To address this issue, we quantify interpersonal trust by analyzing the social interaction frequencies between users and their friends on Facebook. We consider bidirectional interacting data in OSNs to deconstruct a user's social behavior and apply principal component analysis to estimate interpersonal trust. A Facebook app, itrust, is developed to collect interaction data and calculate interpersonal trust. Results show that itrust achieves more accurate interpersonal trust measurements than existing methods.
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