The effects of algorithmic content selection on user engagement with news on Twitter

• In this article, we investigate how Twitter's switch from a reverse-chronological timeline to algorithmic content selection in March 2016 influenced user engagement with tweets published by German newspapers. To mitigate concerns about omitted variables, we use the Facebook postings of these newspapers as a counterfactual. We find that the number of likes increased by 20% and the number of retweets by 15% within a span of 30 days after the switch. Importantly, our results indicate a rich-get-richer effect, implying that initially more popular outlets and news topics benefited the most. User engagement also increased more for sensationalist content than quality news stories.

Subject headings

SAMHÄLLSVETENSKAP  -- Medie- och kommunikationsvetenskap -- Medievetenskap (hsv//swe)

SOCIAL SCIENCES  -- Media and Communications -- Media Studies (hsv//eng)

Keyword

Algorithm bias

Facebook

news quality

social media

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Publication and Content Type

ref (subject category)

art (subject category)