This study examines whether media salience influenced the activation of COVID-19 social restriction policies (PSBB) in Indonesia’s decentralized governance system. Media effects theories, particularly the CNN effect, suggest that intensive news coverage can exert direct pressure on policymakers, yet evidence from domestic and decentralized contexts remains limited. Using a daily dataset, this study analyzes the temporal relationship between PSBB activation, national news coverage from CNN Indonesia, and COVID-19–related Twitter (X) activity. The study employs lagged logistic regression, Granger causality tests, distributed lag models, and social network analysis to assess both temporal influence and discursive prominence. The analysis suggests that, at the level of national PSBB activation, decisions were more closely aligned with institutional dynamics and decentralized authority structures than with immediate spikes in national media coverage. However, because the models do not explicitly compare provinces or districts, the findings should not be read as a comprehensive test of decentralization across Indonesia’s regions. Instead, decentralization is used here to explain why central authorities may struggle to convert high media visibility into rapid, coordinated restrictions in a fragmented governance environment.
Tatak Setiadi (Sun,) studied this question.