Cultural Variance in Reception and Interpretation of Social Media COVID-19 Disinformation in French-Speaking Regions

Int J Environ Res Public Health. 2021 Nov 30;18(23):12624. doi: 10.3390/ijerph182312624.


Digital communication technology has created a world in which media are capable of crossing national boundaries as never before. As a result, language is increasingly the salient category determining individuals' media consumption. Today, a single social media post can travel around the world, reaching anyone who speaks its language. This poses significant challenges to combatting the spread of disinformation, as an ever-growing pool of disinformation purveyors reach audiences larger than ever before. This dynamic is complicated, however, by the diversity of audience interpretations of message content within a particular language group. Both across and within national boundaries, a single message may be subject to a variety of interpretations depending on the cultural experiences and identities of its recipients. This study explores that dynamic through analysis of French language anti-vaccine and COVID-denialist disinformation. Using qualitative coding methodology, a team of researchers empirically identify common and far-reaching patterns of Francophone COVID disinformation narratives and rhetoric. These narratives and rhetorics are then subjected to hermeneutic close reading to determine likely variations in their reception across different French-speaking cultures. Data were gathered and analyzed between the dates of 24 March 2021 and 27 April 2021. Results of this study indicate the need for awareness on the part of public health officials combatting COVID disinformation online, for both the transnational reach of disinformation targeting speakers of a single language and for variations in meaning and salience across cultures within that language group.

Keywords: COVID-19; conspiracy theories; disinformation; francophone; misinformation; persuasion; qualitative coding; social media.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • COVID-19*
  • Disinformation
  • Humans
  • Language
  • SARS-CoV-2
  • Social Media*