The effects of algorithmic content selection on user engagement with news on Twitter
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3AILZ9J3RE" target="_blank" >RIV/00216208:11320/23:ILZ9J3RE - isvavai.cz</a>
Result on the web
<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85165058289&doi=10.1080%2f01972243.2023.2230471&partnerID=40&md5=1612d4a759b2b7864fe3207cbcb6e359" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85165058289&doi=10.1080%2f01972243.2023.2230471&partnerID=40&md5=1612d4a759b2b7864fe3207cbcb6e359</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1080/01972243.2023.2230471" target="_blank" >10.1080/01972243.2023.2230471</a>
Alternative languages
Result language
angličtina
Original language name
The effects of algorithmic content selection on user engagement with news on Twitter
Original language description
"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. © 2023 The Author(s). Published with license by Taylor & Francis Group, LLC."
Czech name
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Czech description
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Classification
Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
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Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
"Information Society"
ISSN
0197-2243
e-ISSN
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Volume of the periodical
39
Issue of the periodical within the volume
5
Country of publishing house
US - UNITED STATES
Number of pages
19
Pages from-to
263-281
UT code for WoS article
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EID of the result in the Scopus database
2-s2.0-85165058289