Social networks analysis of anticorruption messages on Twitter

Abstract

Corruption poses a serious threat to a nation’s progress and undermines public trust in the government. Therefore, it is often referred to as an extraordinary crime. Despite numerous measures being taken, it cannot be denied that corruption still occurs frequently. Thus, in addition to focusing on combating corruption, new approaches are important for disseminating anticorruption messages through various media, including social media. This study examines communication patterns, social network structures, key actors, and their roles in anticorruption messages on Twitter using Social Network Analysis (SNA) methods. Data collection techniques involve text mining or web crawling based on keywords using Gephi 0.97. The data was collected in December 2022, coinciding with the celebration of International Anticorruption Day (Hakordia). The results indicate that analysis units such as density, diameter, average path length, components, and modularity suggest that communication between actors in the network tends to be one-way, with some nodes serving as key actors. Interactions among Twitter users are minimal, with little or almost no reciprocal communication. Based on the patterns observed from the network of anticorruption messages and campaigns, the study reveals an asymmetrical communication network. In terms of actor centrality statistics, those with the highest centrality values are @kpk_ri, @democrazymedia, @tvonenews, @cnnindonesia, and @nazaqistsha. Each of these five actors plays a specific role in the network, depending on their backgrounds. This study concludes that in addition to government actors, mass media and even individuals play a crucial role in disseminating and campaigning for anticorruption messages.