Analysis Content Type and Emotion of the Presidential Election Users Tweets using Agglomerative Hierarchical Clustering
DOI:
10.33395/sinkron.v8i3.12616Keywords:
Twitter, Emotion, Presidential Election, TF-IDF Vectorizer, Agglomerative Hierarchical ClusteringAbstract
Over the past few years, social media has become essential for getting up-to-date information and interacting online. During presidential elections in Indonesia, Twitter has grown as a crucial platform for expressing opinions and sharing information. This study focuses on analyzing the content types and emotions of tweets related to Anies Baswedan, one of the presidential candidates. The results show a variety of discussions, including support, criticism, and discussion of policies for the 2024 presidential candidate. Clustering enables meaningful information extraction from vast Twitter data. Data were clustered using Agglomerative Hierarchical Clustering, which resulted in the identification of 10 clusters. With 4 clusters containing opinion content and 6 clusters containing information content. In addition, 6 clusters reflect excitement, 3 reflect expectations, and 1 reflect doubt. This research provides insights into the Twitter conversation around the 2024 presidential election, providing an understanding of content and emotions expressed by users.
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Copyright (c) 2023 Cika Carissa Sujadi, Yuliant Sibaroni, Aditya Firman Ihsan
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