Public Sentiment as a Measure of Human Adjustment to Government Interventions During COVID-19: A Mixed-Method Analysis

The COVID-19 pandemic prompted the rapid implementation of non-pharmaceutical interventions (NPIs) in South Africa, necessitating significant public adjustments. This longitudinal study investigates patterns of adaptation by analysing sentiment trends on Twitter through the lens of the W-curve model of cultural adjustment, which delineates four phases: honeymoon, culture shock, adjustment, and recovery. The study makes three key contributions. First, it demonstrates that public sentiment is a predictive index of human adjustment, initially reflecting a U-curve pattern that later stabilised into a complete W-curve. Second, it positions public sentiment as a real-time feedback mechanism for public health policy, suggesting that greater awareness of adjustment trajectories might have precluded the need for military deployment. Third, it empirically validates the theoretical relevance of U-curve and W-curve models in understanding public responses during national crises. These findings underscore the importance of integrating sentiment analysis into policy evaluation frameworks to support adaptive and context-sensitive governance.