Social Media Influence Operations and Political Manipulation in Nigerian Democratic Processes

This study examines coordinated social media influence operations and their effect on Nigerian democratic processes, providing an empirical analysis of the tactics, scale, and impact of political manipulation through digital platforms. Social media influence operations, defined as coordinated inauthentic behaviour using fake accounts, bots, and paid human amplifiers to artificially shape political discourse, have been identified in multiple global election contexts but remain understudied in the Nigerian setting. This study employs a computational social science methodology, analysing a dataset of 1.2 million tweets related to the 2023 Nigerian general elections using machine learning-based bot detection algorithms (Botometer) to identify potentially inauthentic accounts. Network analysis maps amplification structures. Qualitative analysis of account content characterises narrative strategies. A survey of 350 Nigerian social media users assesses awareness of influence operations and effects on political trust. Findings reveal that approximately 12 percent of highly active political Twitter accounts during the election period show bot-like behavioural signatures. These accounts disproportionately amplify content supporting one candidate and attack opposing candidates through coordinated trending hashtag operations. Three distinct operational clusters are identified through network analysis, each with different primary targeting strategies. Public awareness of influence operations is low (28 percent of survey respondents). Trust in social media political information is significantly lower among those who are aware of manipulation. The study contributes original computational evidence of social media influence operations in a Nigerian election context and recommends platform transparency reporting requirements and media literacy campaigns.

Keywords: social media, influence operations, political manipulation, Nigeria, elections.