A Computational Analysis of Media Coverage and the Reframing of Steve Biko and Black Consciousness during the Fallist Movements (2013– 2018)
Open Access DepositedLegacy on the Front Page
This thesis investigates how Steve Biko and the Black Consciousness (BC) philosophy were represented in eight major South African English-language newspapers from 2013 to 2018, particularly in the context of the #RhodesMustFall and #FeesMustFall movements. Collectively known as the Fallist movements, these student-led campaigns formed an ideologically linked wave of post-apartheid resistance targeting institutional racism, colonial legacies, and structural inequality in higher education. Drawing on a corpus of over 2,100 newspaper articles, the study employs a multi-method computational text analysis to examine thematic structures, sentiment dynamics, and affective framings of Biko and BC. It finds that while explicit references to Fallist movements are often absent in Biko-related coverage, themes of education, youth, and institutional critique become increasingly prominent during this period, before tapering off in the post-Fallist era. These discursive realignments suggest a symbolic resonance with Fallist ideology, despite the lack of direct references. Biko and his legacy are extensively used as a moral touchstone to critique contemporary politics and ongoing racial inequalities across the period studied
however, the Fallist moment marked a shift from retrospective, commemorative emotions to aspirational and future-oriented framings. The thesis also conducts an exploratory comparative analysis of Black and non-Black press, finding that Black press outlets appear to be more attuned to the epistemic and affective registers of student movements, potentially opening new directions for future research on media tradition and political alignment. These findings underscore how media memory selectively rearticulates radical legacies when confronting contemporary activism—especially those not uniformly embraced by the mass media. Methodologically, the study contributes to media sociology and memory studies by demonstrating the effectiveness of computational approaches in surfacing latent ideological structures in journalistic discourse surrounding iconic political figures in South Africa. While the study offers novel insights, it is not without limitations. Like any attempt to employ computational text analysis in social science, the use of machine learning models, though fine-tuned, may insufficiently capture the cultural and linguistic specificity of South African media texts, thus risking the oversimplifying a more complex editorial landscape. Future research could benefit from integrating deeper qualitative analysis with computational methods to fully capture the sociopolitical texture of media representation and symbolic discourse.
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