Open Access Journal

ISSN: 2183-2463

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Populist Disinformation: Exploring Intersections between Online Populism and Disinformation in the US and the Netherlands

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Abstract:  The discursive construction of a populist divide between the ‘good’ people and ‘corrupt’ elites can conceptually be linked to disinformation. More specifically, (right-wing) populists are not only attributing blame to the political elites, but increasingly vent anti-media sentiments in which the mainstream press is scapegoated for not representing the people. In an era of post-truth relativism, ‘fake news’ is increasingly politicized and used as a label to delegitimize political opponents or the press. To better understand the affinity between disinformation and populism, this article conceptualizes two relationships between these concepts: (1) blame attributions to the dishonest media as part of the corrupt elites that mislead the people; and (2) the expression of populist boundaries in a people-centric, anti-expert, and evidence-free way. The results of a comparative qualitative content analysis in the US and Netherlands indicate that the political leaders Donald Trump and Geert Wilders blame legacy media in populist ways by regarding them as part of the corrupt and lying establishment. Compared to left-wing populist and mainstream politicians, these politicians are the most central players in the discursive construction of populist disinformation. Both politicians bypassed empirical evidence and expert knowledge whilst prioritizing the people’s truth and common sense at the center stage of honesty and reality. These expressions resonated with public opinion on Facebook, although citizens were more likely to frame mis- and disinformation in terms of ideological cleavages. These findings have important implications for our understanding of the role of populist discourse in a post-factual era.

Keywords:  disinformation; fake news; misinformation; populism; social networks

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DOI: https://doi.org/10.17645/pag.v8i1.2478


© Michael Hameleers. This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 license (http://creativecommons.org/licenses/by/4.0), which permits any use, distribution, and reproduction of the work without further permission provided the original author(s) and source are credited.