Topic Modelling and Sentiment Analysis on YouTube Sustainable Fashion Comments | |
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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 |
相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/125042 ) |
SDGS | 產業創新與基礎設施 |