Harnessing Collective Intelligence for Translation: An Asssessment of Crowdsourcing as a Means of Bridging the Canadian Linguistic Digital Divide

Abstract

This study attempts to shed light on the efficacy of crowdsourcing as a means of translating web content in Canada. Within, we seek to explore and understand if a model can be created that can estimate the effectiveness of crowdsourced translation as a means of bridging the Canadian Linguistic Digital Divide. To test our hypotheses and models, we use structural equation modeling techniques coupled with confidence intervals for comparing experimental crowdsourced translation to both professional and machine translation baselines. Furthermore, we explore a variety of factors which influence the quality of the experimental translations, how those translations performed in the context of their source text, and the ways in which the views of the quality of the experimental translations were measured before and after participants were made aware of how the experimental translations were created.