Identifikasi Topik Populer Fandom Alien Stage pada Round 6 Berdasarkan Komentar Youtube Menggunakan Text Mining

Aviliani Putri; Rouli Doharma

doi:10.55606/juitik.v6i1.2019

Authors

Aviliani Putri Institut Sosial dan Teknologi Widuri
Rouli Doharma Institut Sosial dan Teknologi Widuri

DOI:

https://doi.org/10.55606/juitik.v6i1.2019

Keywords:

Alien Stage, Fandom, Ivan, Text Mining, YouTube

Abstract

The importance of knowing how fandoms respond to something they are interested in, whether it's K-Pop, Anime, or Movies. One of the popular fandoms right now is the Alien Stage fandom, a work of animation created by VIVINOS. This aims to understand popular topics widely discussed among the fandom, especially on applications like YouTube comment sections, which serve as a place for fandom interaction to foster close relationships with each other. However, due to the large volume and number of comments in the comment section, this sometimes presents a challenge for identification. Therefore, using text mining can be a solution to find out popular topics among fandoms, which involves collecting comment data using data crawling, cleaning it during the data preprocessing stage, and extracting keywords using TF-IDF to produce the top 10 keywords. The results show that the characters of Ivan and Till became very popular and widely discussed topics, demonstrating how fans felt emotional connections to the characters and storylines in ROUND 6.

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