Polarization-Affinity of Indonesian Political Figures: Insights from Network of Twitter Followers with Modularity Clustering and Linear Arrangement

This study investigates political polarization in Indonesia using Twitter follower networks of political figures. This is particularly evident in interactions on social media, primarily through followers of political accounts on Twitter. The more users who follow figures or media from a single political spectrum, the higher the level of polarization among followers, indicating a tendency to be exposed to one-sided political views. This study utilizes a dataset of the Twitter accounts of Indonesian political figures and their followers. We applied modularity clustering and minimum linear arrangement to reveal patterns of political affiliation and polarization. Subsequently, Minimum Linear Arrangement is employed to organize and visualize these groups, providing a more structured view of political affinity distribution within the network. This approach offers deep insights into how followers of political accounts are fragmented along the political spectrum and illustrates the level of polarization among supporters of political figures. Our findings highlight fragmented communities along the political spectrum, with modularity clustering scoring 0.20. The findings of this study also analyze political affinity based on Twitter follower data, offering a basis for understanding potential voter engagement and public participation in elections through digital platforms.