Supporting human decision-making online using information-trustworthiness metrics

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Abstract

The vast amount of information available online places decision makers wishing to use this content in an advantageous but also very difficult position. The advantages stem from the volume of content from a variety of sources that is readily available; the difficulties arise because of the often unknown quality and trustworthiness of the information - is it fact, opinion or purely meant to deceive? In this paper we reflect on and extend current work on information trust and quality metrics which can be used to address this difficulty. Specifically, we propose new metrics as worthy of consideration and the new combinatorics required to take measurements of the various trust factors into a single score. These feed into our existing overarching policy-based approach that uses trustworthiness metrics to support decision-making online. © 2013 Springer-Verlag Berlin Heidelberg.

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Nurse, J. R. C., Creese, S., Goldsmith, M., & Rahman, S. S. (2013). Supporting human decision-making online using information-trustworthiness metrics. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8030 LNCS, pp. 316–325). Springer Verlag. https://doi.org/10.1007/978-3-642-39345-7_33

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