Algorithmic recommendations and echo chambers: User awareness in the UAE

Abstract

Algorithmic recommendations have radically transformed the ability to select content based on social media users' preferences and behaviours, impacting news diversity and raising concerns regarding how individual beliefs and preferences affect the choice of news content. This, in turn, has led to the emergence of so-called echo chambers. This study examines the relationship between public awareness of algorithmic recommendations and awareness of the echo chamber phenomenon, focusing on its cognitive dimension. Using a survey of 446 social media users in the United Arab Emirates, a country characterised by a high diversity of nationalities and high social media usage, this study adopted algorithmic gatekeeping as a theoretical framework and proposed a conceptual framework to explore the factors influencing users' awareness of echo chambers. The findings suggest that algorithmic awareness, diversity of news recommendations, and an understanding of how algorithmic gatekeeping works significantly impact users’ awareness of echo chambers. However, demographic factors (such as age or gender), which were included as a controlling variable, had no influence. The results demonstrate the importance of adopting digital media literacy concepts, spreading awareness of how algorithms are employed by social media platforms, and supporting digital initiatives that enhance the diversity of news content provided to users.

Keywords Algorithmic gatekeeping; Algorithmic recommendations; Echo chamber; News diversity; Social media; Trust