Clustering Analysis of Comments on Regional Promotion Videos

Abstract

A growing number of local governments are utilizing video-sharing platforms as a means of regional promotion, producing videos designed to showcase the unique attractions of their respective areas. On these platforms, viewers can freely post comments on the videos. While many comments express positive opinions and favorable impressions, some include defamatory or malicious content. This study analyzes comments posted on regional promotion videos produced by local governments using text mining techniques. By applying document clustering to the comments associated with highly rated videos, the study aims to identify the key themes and content characteristics that contribute to high evaluations.