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From Fake to Junk News, the Data Politics of Online Virality

Abstract : ‘Fake news’ is a key subject of data politics, but also a tricky a one. As this chapter aims to show, various phenomena signified by this misleading label have little in common, except being opposite to the kind of algorithmic intelligence that most other chapters present as the main concern of data politics. This does not mean that ‘fake news’ is not related to computational analytics or political intentions, but it does mean that this relation is not straightforward. To discuss this relation, I will go through a three-stage argument. First, I will criticise the notion of ‘fake news’, dismissing the idea that this type of misinformation can be defined by its relationship to truth. Second, I will propose a different definition of this phenomenon based on its circulation rather than of its contents. Third, I will reintroduce the connection to data politics, by describing the economic, communicational, technological, cultural and political dimensions of junk news.
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https://hal.archives-ouvertes.fr/hal-02003893
Contributor : Tommaso Venturini <>
Submitted on : Friday, February 1, 2019 - 2:17:30 PM
Last modification on : Wednesday, December 9, 2020 - 3:04:54 PM
Long-term archiving on: : Thursday, May 2, 2019 - 9:26:37 PM

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Tommaso Venturini. From Fake to Junk News, the Data Politics of Online Virality. Didier Bigo, Engin Isin, Evelyn Ruppert. Data Politics: Worlds, Subjects, Rights, Routledge, 2019, 9781138053250. ⟨hal-02003893⟩

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