Topic Modeling in 2019 Indonesian Election News Titles Using the Latent Dirichlet Allocation (LDA) Method
Pemodelan Topik dalam Judul Berita Pemilu 2019 Indonesia Menggunakan Metode Latent Dirichlet Allocation (LDA)
DOI:
https://doi.org/10.21070/ups.8741Keywords:
Latent Dirichlet Allocation, General Elections, Topic ModelingAbstract
This research examines the reporting of the 2019 General Election in Indonesia, focusing on analysis using the Latent Dirichlet Allocation (LDA) method. With comprehensive data processing and text analysis, the study successfully identifies key topics in the media narrative related to the election. These topics include the dynamics of the general election, such as campaign strategies and the influence of significant political figures, as well as logistical and administrative elements of the election. The LDA method, enhanced with interactive visualization using pyLDAvis, allows for detailed analysis of how the media approaches these issues. The results of this research provide deep insights into how various aspects of the election are perceived and presented to the public through the media. These findings are highly relevant not only for understanding the broader context of the election but also in the context of designing effective political communication strategies for the future.
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