Diffusion of protest behaviour: Analysing the July 2021 civil unrest in South Africa through sentiment analysis and topic modelling

The jailing of former South African President Jacob Zuma in July 2021 ignited protests in KwaZulu-Natal and quickly spread to Johannesburg and Pretoria. Initially peaceful, these demonstrations escalated into widespread looting and violence, culminating in the deaths of 354 individuals. This study employs a mixed-methods approach by integrating machine learning and qualitative analysis to examine the dynamics of the unrest using Twitter data from multiple South African provinces. Tweets were manually annotated for sentiment (positive, negative, neutral), and inter-annotator agreement was measured using Fleiss' Kappa, yielding a score of 0.27, indicative of fair consensus. The most accurate sentiment classification model labelled the remaining dataset, enabling the temporal tracking of sentiment and protest diffusion. Findings underscore the role of economic inequality, political instability, and racial tensions in fuelling the unrest. Also, the lifecycle of the protests progresses from mobilisation to looting, violence, and change, which was confirmed through social media discourse. The study highlights the utility of social media analytics in complementing investigative journalism and informing state responses to urban crises. It contributes to the growing literature on collective violence and the diffusion of protest behaviour in digitally networked societies.