TWITTER SOCIAL NETWORK ANALYSIS AND SENTIMENT IDENTIFICATION OF “VAKSIN BOOSTER” KEYWORD

Abstract

Abstract. The low acceptance level and limited coverage of booster vaccines, despite their critical importance for public health, highlight the need for deeper insights into societal perceptions and behaviors. Social networks, as a significant medium for information dissemination, offer a valuable opportunity to understand public discourse and identify influential factors. This study leverages graph topology analysis to map and analyze the dynamics of vaccine-related discussions within social networks. By identifying key individuals who play pivotal roles in spreading booster vaccine information, the analysis reveals the structure and flow of information within the network. Furthermore, sentiment analysis indicates that neutral interactions dominate these discussions, followed by negative and positive sentiments. Notably, the neutral content largely pertains to travel procedures, which aligns with the "mudik" tradition during the data collection period. These findings provide a framework for understanding the sociotechnical landscape of vaccine acceptance and offer actionable insights for designing targeted, effective strategies to enhance booster vaccine uptake.