Towards a computational model of information trust

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Information has been an essential element in the development of collaborative and cooperative frameworks. From decision making to the attainment of different goals, people have been relatively adept at making judgments about the trustworthiness of information, based on knowledge and understanding of a normative model of information. However, recent events, for example, in elections and referenda, have stretched the ability of people to be able to measure the integrity and trustworthiness of information online. The result has been an erosion of trust in information online, its source, its value, and the ability to help one determine the trustworthiness of a piece of information. The situation is made more complex by social networks since social media have made the spread of (potentially untrustworthy) information more accessible and faster. We believe that this has exacerbated the need to assist humans in their judgment of the trustworthiness of information. In this work, we present a social cognitive construct: a trust model for information. We present our trust model, which we incorporate into an application to highlight misleading information, with the experimental result on users’ perception of the working of the model. Finally, we highlight the challenges faced in this research and future work.
Computational trust, Security, AI, HCI, ML