Abstract
This chapter shows how algorithms affect journalistic practices and which implications can be drawn from that for audience trust in media. Algorithms, as encountered in e-shopping or on social media, are now commonly found in daily life, and journalism is no exception. To assess how journalism makes use of algorithms to both distribute and create content, two technologies are considered in this chapter: content personalisation and the automated creation of texts. Both technologies come with various implications and challenges for how news are perceived and written, both positive and negative. While, for example, content personalisation helps users to curate their news stream according to their interests, such a highly personalised news stream may enclose users in a filter bubble. The case of automation in news writing is even more complex, as, on the one hand, automation has the potential to free journalists from routine tasks and allows for more investigative reporting, but on the other hand produces quite simplistic articles that journalists feel do not adhere to their standards. Both cases demonstrate that a new social and economic relationship between technology and journalism develops in the newsroom. Thus, news outlets should be transparent about how they employ algorithmic content distribution and creation to ensure that these technologies do not undermine trust in media.
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Notes
- 1.
Wordsmith is distributed by Automated Insights, see https://automatedinsights.com/wordsmith (last accessed March 8, 2019).
- 2.
See http://www.wibbitz.com/ (last accessed March 8, 2019).
- 3.
The Washington Post Medal Bot for the 2018 Olympics can be found here: https://twitter.com/wpolybot (last accessed March 8, 2019). The Twitter account for the 2016 Rio Olympics has since been deleted.
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Kunert, J. (2019). Journalists, Meet Your New Colleague Algorithm: The Impact of Automation on Content Distribution and Content Creation in the Newsroom. In: Osburg, T., Heinecke, S. (eds) Media Trust in a Digital World. Springer, Cham. https://doi.org/10.1007/978-3-030-30774-5_10
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