Rina Noviana, Isram Rasal
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引用次数: 1

摘要

防弹少年团(BTS, Bangtan Sonyeondan)是目前在印尼青少年中很受欢迎的韩国组合之一,粉丝们在社交媒体Twitter上发表了很多褒贬不一的评论。判断这些评论是积极的还是消极的方法是进行情绪分析。执行数据分析的阶段是预处理以清理数据、单词加权、将数据标记为正类和负类、分类以及使用饼图进行数据可视化。在本研究中,使用朴素贝叶斯和支持向量机进行比较,结果朴素贝叶斯的准确率得分为79%,支持向量机的准确率得分为81%。在这两种方法中,支持向量机获得了更高的准确率得分,并且情绪分析显示,从Twitter用户获得的评论以积极为主。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PENERAPAN ALGORITMA NAIVE BAYES DAN SVM UNTUK ANALISIS SENTIMEN BOY BAND BTS PADA MEDIA SOSIAL TWITTER
BTS or Bangtan Sonyeondan is one of the vocal groups originating from South Korea, which is currently popular among Indonesian teenagers, resulting in many fans providing positive and negative comments through Twitter social media. The method used to determine whether these comments are positive or negative is by conducting sentiment analysis. The stages to perform data analysis are Preprocessing to clean the data, word weighting, labeling data into positive and negative classes, classification, and data visualization using pie charts. In this study, Naive Bayes and Support Vector Machine, were used for comparison, result of an accuracy score is 79% for Naive Bayes and 81% for Support Vector Machine. Among these two methods, Support Vector Machine achieved a higher accuracy score, and the sentiment analysis revealed that the comments obtained from Twitter users are predominantly positive.
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