Topic Modelling and Sentiment Analysis on YouTube Sustainable Fashion Comments
學年 112
學期 1
出版（發表）日期 2023-12-27
作品名稱 Topic Modelling and Sentiment Analysis on YouTube Sustainable Fashion Comments
作品名稱（其他語言）
著者 Hsu-Hua Lee; MTN Nguyen
單位
出版者
著錄名稱、卷期、頁數 Journal of New Media 5(1), p.65-80
摘要 YouTube videos on sustainable fashion enable the public to gain basic knowledge about this concept. In this paper, we analyse user comments on YouTube videos that contain sustainable fashion content. The paper’s main objective is to help content creators and business managers effectively understand the perspectives of viewers, thus improving video quality and developing business. We analysed a dataset of 17,357 comments collected from 15 sustainable fashion YouTube videos. First, we use Latent Dirichlet Allocation (LDA), a topic modelling technique, to discover the abstract topics. In addition, we use two approaches to rank these topics: ranking based on proportion and Rank-1 method. Second, we apply sentiment analysis to identify the user’s emotional tone in the comments. As a result, 14 topics were identified. The most common positive and negative scores are 1 and −1, respectively. In total, there are 28.42% positive comments, 22.35% negative comments and 49.23% neutral comments.
關鍵字 Topic modelling;sentiment analysis;latent dirichlet allocation;natural language processing;sustainable fashion;YouTube comments
語言 en_US
ISSN 2579-0129;2579-0110
期刊性質 國外
收錄於
產學合作
通訊作者
審稿制度 否
國別 USA
公開徵稿
出版型式 ,電子版,紙本
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機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/125042 )

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