Crowdsourcing as a Knowledge-Search Method in Digital Journalism

Abstract

This article examines crowdsourcing as a knowledge-search method and an open journalistic practice in digital journalism. The study draws on data from four cases in which professional journalists used crowdsourcing in their investigations. Crowdsourcing resulted in an efficient knowledge discovery and a continuous flow of tips to journalists and thus benefited journalistic investigations. The horizontal and vertical transparency in crowdsourced journalism supported the knowledge-search process. However, the high volume of submissions in some cases made the journalists compromise the journalistic norm of data verification, which resulted in publishing unverified information. Crowdsourcing as an open journalistic practice thus ruptures journalistic norms and creates pressure for new ones to emerge, such as blended responsibility, in which the responsibility for data accuracy is shared by the journalists and the readers. The article extends the examination of open journalistic practices and contributes to the understanding of their impact on digital journalism.