Framing Patterns of Influencers’ Hate Speech on X During the 2023 Presidential Election Campaign in South-West Nigeria

Abstract

Digital platforms such as X (formerly Twitter) have expanded the influence of social media influencers in Nigeria’s online political communication, but have also intensified the spread of hate speech during elections. This study examines how selected influencers framed hate speech during the 2023 presidential election campaign. Using quantitative content analysis, posts from three purposively selected influencers; @SeyiLaw1, @AisahYesufu, and @DemolaRewaju, representing APC, LP and PDP were retrieved on Twitter, screened through a validate hate-speech lexicon, and coded into ten framing categories. A total of 1,634 posts were identified and 580 posts consists of hate speech content which were analysed using descriptive statistics, one-way ANOVA, and Tukey’s HSD test to test differences in the frames. Findings show that influencers employed diverse framing strategies, with foreign interference and economic marginalisation emerging as the most prevalent frames, while victimhood appeared least. ANOVA results indicate statistically significant overall differences in framing patterns across influencers, although post-hoc comparisons revealed no significant pairwise differences. The study contributes to scholarship on digital communication by demonstrating how influencer-generated frames shape the visibility and circulation of hate speech during elections. It also highlights the need for strengthened digital governance and targeted interventions to mitigate the risks associated with influencer-driven polarisation.