Designing for information quality in the era of repurposable crowdsourced user-generated content

Abstract

Conventional wisdom holds that expert contributors provide higher quality user-generated content (UGC) than novices. Using the cognitive construct of selective attention, we argue that this may not be the case in some crowd-sourcing UGC applications. We argue that crowdsourcing systems that seek participation mainly from contributors who are experienced or have high levels of proficiency in the crowdsourcing task will gather less diverse and therefore less repurposable data. We discuss the importance of the information diversity dimension of information quality for the use and repurposing of UGC and provide a theoretical basis for our position, with the goal of stimulating empirical research.