Viral journalism. Strategy, tactics and limitations of the fast spread of content on social media: case study of the UK quality publications

Denisova, A. 2022. Viral journalism. Strategy, tactics and limitations of the fast spread of content on social media: case study of the UK quality publications. Journalism. 24 (9), pp. 2899-2913. https://doi.org/10.1177/14648849221077749

TitleViral journalism. Strategy, tactics and limitations of the fast spread of content on social media: case study of the UK quality publications
TypeJournal article
AuthorsDenisova, A.
Abstract

Journalism has been under much strain in the recent decades. It has had to adapt to the changing rhythms of media consumption as much as to the benevolence of social media networks that constantly change algorithms of how journalism is displayed. At the same time, viral communication of all sorts – from memes to GIFs and widespread amateur entertaining videos – is seen by millions. The purpose of this article is to examine the effort of online journalism to compete with viral storytelling. ‘Viral journalism’ is defined as the strategy and tactics to promote quality media stories on the internet in order to gain maximum exposure and sharing. This phenomenon is not to be mistaken with ‘clickbait’, which entails catchy, but often misleading, headlines. This article is based on qualitative interviews with a variety of social media editors and other journalists in the UK: from The Economist to The Guardian. It reveals that quality UK media deploy a range of inventive engaging tactics, but reject virality as a long-term strategy. The media professionals interviewed raised many concerns about virality, indicating that exploiting viral technics may results in reputational damage and alienating loyal readers.

Keywordsdigital journalism
clickbait
social media
audience engagement
memes
JournalJournalism
Journal citation24 (9), pp. 2899-2913
ISSN1464-8849
1741-3001
Year2022
PublisherSage
Publisher's version
License
CC BY-NC 4.0
File Access Level
Open (open metadata and files)
Digital Object Identifier (DOI)https://doi.org/10.1177/14648849221077749
Publication dates
Published online24 Mar 2022

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