Use of Big Data in Political Communication Analysis: Forming a Targeting and Electorate Segmentation Strategy

Abstract

In this digital era, political communication has become increasingly complex with the emergence of various social media platforms and information technology. This allows for greater interaction between political leaders, parties and the electorate. In this context, the use of Big Data has become crucial in collecting, analyzing and understanding the political behavior patterns of the electorate. This research aims to explore the use of Big Data in the context of political communication analysis, especially in forming targeting and electorate segmentation strategies. Through this approach, it is hoped that an effective method can be found in understanding mass political preferences. This research uses a qualitative and quantitative approach by analyzing Big Data data from various social media platforms, online surveys and other digital data sources. Statistical analysis and machine learning techniques are also used to identify patterns of electoral behavior. The research results show that the use of Big Data in political communication analysis provides deep insight into the preferences and needs of the electorate. By utilizing available data, targeting and electorate segmentation strategies can be prepared more precisely and effectively. The conclusion of this research is the analysis of political communication, the use of Big Data has proven its value in forming targeting and electorate segmentation strategies. With an integrated approach between qualitative and quantitative data, political leaders and parties can better understand political dynamics and increase the effectiveness of communication with the electorate.