Formulation of a model for the dissemination of government policy issues in online media and YouTube in Indonesia

Abstract

The rapid expansion of digital media has reshaped political communication in Indonesia, creating fragmented pathways through which issues diffuse across mainstream and participatory platforms. Despite this transformation, limited research has examined how public debates surrounding major government programs spread within hybrid media systems or what mechanisms determine issue centrality. This study addresses that gap by analyzing discourse dynamics related to Free Nutritious Meals (MBG) and Danantara. Using a sequential explanatory mixed-methods design, the study first mapped structural patterns quantitatively and then deepened interpretation through qualitative analysis. The dataset comprised 1,696 online news articles, 363 YouTube videos, more than 26 million user comments, and survey responses from 620 participants, offering a comprehensive representation of Indonesia’s digital discourse landscape. Structural Topic Modeling (STM) was used to identify dominant issues, while Social Network Analysis with QAP and MRQAP assessed co-occurrence patterns. Engagement metrics captured audience polarization, and thematic plus Critical Discourse Analysis (CDA) examined contrasts between institutional and participatory framing. Findings reveal that issue frequency—not semantic similarity—is the strongest predictor of diffusion. High-frequency issues consistently emerged as hubs in discourse networks. Mainstream media largely legitimized policy through socio-economic frames, whereas YouTube channels amplified criticism, satire, and counter-narratives, reflecting sharp audience polarization. Qualitative analysis reinforced these divergences, demonstrating how institutional and participatory media construct competing interpretations of the same policies. The integrated findings produced a conceptual model—”Frequency-Driven Co-occurrence”—which explains how mention intensity drives issue centrality and narrative evolution. The model advances agenda-setting and framing theories by shifting emphasis from semantic similarity to issue salience as the primary diffusion mechanism in hybrid media environments. Practical implications highlight the need for transparency, stronger digital literacy, and collaboration with credible influencers to reduce polarization, while future research should examine longitudinal trajectories, algorithmic amplification, and affective dynamics in digital discourse.

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