TY  - EJOU
AU  - Lee, Hsu-Hua 
AU  - Nguyen, Minh T. N. 

TI  - Topic Modelling and Sentiment Analysis on YouTube Sustainable Fashion Comments
T2  - Journal of New Media

PY  - 2023
VL  - 5
IS  - 1
SN  - 2579-0129

AB  - 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.
KW  - Topic modelling; sentiment analysis; latent dirichlet allocation; natural language processing; sustainable fashion; YouTube comments

DO  - 10.32604/jnm.2023.045792