Analisis Topik Tagar Covidindonesia pada Instagram Menggunakan Latent Dirichlet Allocation

Kevin Rafi Adjie Putra Santoso, Asmaul Husna, Nadia Widyawati Putri, Nur Aini Rakhmawati
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引用次数: 3

Abstract

In this era, technology is increasingly sophisticated, this is evidenced by the number of people using the internet via cell phones, laptops, and other communication tools. One of the developments of this technology is social media such as Instagram. Along with technological developments, Instagram users can upload and share photos and videos using hashtags (#) so that other users can find the results of their posts. Instagram has now become one of the social media used by more than 1 billion people in the world. In this study, the authors wanted to know the dominant topics discussed through the hashtag covidindonesia. This research was conducted using the Latent Dirichlet Allocation (LDA) method. The analysis was carried out after doing text mining on 84 captions from various users on Instagram. To determine the optimal number of topics, by looking at the value of perplexity and topic coherence. The results obtained are the top 5 topics that are the content material in the uploaded video. These topics include covidindonesia, covid_19, pandemics in Indonesia, and discussion of covid-19 virus mutations.
Instagram上使用潜在Dirichlet分配的Covidinonesia标签主题分析
在这个时代,技术越来越复杂,通过手机、笔记本电脑和其他通信工具使用互联网的人数证明了这一点。这项技术的发展之一是社交媒体,如Instagram。随着技术的发展,Instagram用户可以使用标签(#)上传和分享照片和视频,这样其他用户就可以找到他们帖子的结果。Instagram现在已经成为全球超过10亿人使用的社交媒体之一。在这项研究中,作者想知道通过标签covididonesia讨论的主要话题。这项研究是使用潜在狄利克雷分配(LDA)方法进行的。该分析是在对Instagram上不同用户的84个字幕进行文本挖掘后进行的。通过考察困惑和话题连贯的价值来确定话题的最佳数量。获得的结果是作为上传视频中的内容材料的前5个主题。这些主题包括冠状病毒病、冠状病毒19、印度尼西亚的流行病以及对新冠肺炎病毒突变的讨论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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12 weeks
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