Media Bias and Information Literacy among Nigerians: The Role of Social Media Algorithms in Nigeria’s Information Landscape

Abstract

Nigeria’s information landscape has changed rapidly as social media platforms increasingly mediate how citizens access, interpret, and share news. While traditional media bias in Nigeria has been widely documented, less attention has been paid to how algorithmic systems on platforms such as Facebook, X (formerly Twitter), TikTok, and YouTube shape public knowledge, amplify misinformation, and influence civic reasoning. This paper examines the intersection of media bias and information literacy in Nigeria, focusing on the role of social media algorithms in shaping visibility, engagement, and credibility within the digital public sphere. Drawing on conceptual literature on media bias, information literacy, and algorithmic governance, alongside qualitative analysis of documented Nigerian cases—including election misinformation, public health crises, and ethno-religious tensions—the study argues that algorithmic curation exacerbates existing structural biases while creating new forms of “algorithmic bias” that disproportionately affect low-literacy and highly vulnerable populations. The paper further demonstrates that limited algorithmic literacy among Nigerians increases susceptibility to misinformation and polarising content. It concludes by proposing a multi-level framework to strengthen information literacy, improve algorithmic transparency, and foster a fairer and more trustworthy Nigerian information ecosystem.