Risks and Opportunities in Automated Newsgathering: First Findings From the Frontline

• In Event: Robots, Machines, and Algorithms: Perspectives on Automated Journalism

Abstract

This article addresses the use of algorithms in news gathering. Specifically it examines the use of three advanced tools that aggregate and filter content from social networks. The first, Geofeedia, allows journalists to search any location for social media. The second, Spike, and the third, Social Sensor, are optimised to identify trending topics. This project analysed the experiences of 81 journalists who used these tools—as well as, for comparison, Twitter—for a period of two weeks, reporting back on the extent to which they helped them: identify news, contacts, and updates on social networks; assess the reliability of contributors; and identify trends in popularity and audience sentiment around stories. The results help in the assessment of the real-world value of such computational tools, show the complex ways they are adopted by end users, and prompt questions about how they might change journalistic practice and the content of news publications.

Authors

• Neil James Thurman, Ludwig-Maximilians-University Munich

• Stephen Schifferes, City U London