Facebook Infodemic in Algeria: A (Factual) Qualitative Content Analysis

Abstract

Untrue and unverified information have their consequences on the public opinion. When the information in the time of a pandemic is false, the case may be worse. An infodemic has emerged with the starting alert of the COVID-19 pandemic. Algerian Facebook users participated in some ways in the dissemination of the infodemic through explaining the symptoms, suggesting preventions, expecting a vaccine, describing the government actions, etc. This dissertation addresses the types of information disorders and infodemic in Algeria. It explores the pandemic-related mis-, dis-, and mal-information shared on Facebook. Besides, it aims at revealing how the linguistic and content features contribute to the (dis)factuality and (in)validity of such information. The study is based on a corpus of forty Facebook posts and it adopts two different qualitative methods. First, a factual analysis is conducted for the purposes of categorizing the information and showing their degrees of harm. Second, a qualitative content analysis is used for the purpose of highlighting the major linguistic features used in those categories of infodemic. The results revealed that misinformation is the common level of shared infodemic among Algerian Facebook users. Besides, the linguistic aspects of the posts contributed to a considerable extent to the verification of the information type and the actors’ intentions to mislead and/or harm.