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Topic Modelling and Sentiment Analysis on YouTube Sustainable Fashion Comments

Hsu-Hua Lee, Minh T. N. Nguyen*

Department of Management Sciences, College of Business and Management, Tamkang University, New Taipei City, 251201, Taiwan

* Corresponding Author: Minh T. N. Nguyen. Email: email

Journal of New Media 2023, 5(1), 65-80. https://doi.org/10.32604/jnm.2023.045792

Abstract

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.

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Cite This Article

H. Lee and M. T. N. Nguyen, "Topic modelling and sentiment analysis on youtube sustainable fashion comments," Journal of New Media, vol. 5, no.1, pp. 65–80, 2023. https://doi.org/10.32604/jnm.2023.045792



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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