Topic Modelling and Sentiment Analysis on YouTube Sustainable Fashion Comments

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题名:	Topic Modelling and Sentiment Analysis on YouTube Sustainable Fashion Comments
作者:	Lee, Hsu-Hua;Nguyen, MTN
关键词:	Topic modelling;sentiment analysis;latent dirichlet allocation;natural language processing;sustainable fashion;YouTube comments
日期:	2023-2-27
上传时间:	2024-02-20 12:06:17 (UTC+8)
出版者:	Tech Science Press
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.
關聯:	Journal of New Media 5(1), p.65-80
DOI:	10.32604/jnm.2023.045792
显示于类别:	[管理科學學系暨研究所] 期刊論文

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