Free descriptive analysis of Review evaluation using tf-idf method
Ryota SAWAUCHI, Takashi Oyama, Teruaki Ito · Sekkei Kougaku, Shisutemu Bumon Kouenkai kouen rombunshuu/Sekkei Kogaku, Shisutemu Bumon Koenkai koen ronbunshu · 2022
This paper describes the free description analysis on review comments evaluation using the tf-idf method, which is one of the machine learning methods. This study selected three types of comics YouTube video an evaluation target, performed machine learning by TF-IDF on the comment of the corresponding YouTube video as subjective free description data, extracted the feature values for each video, and visualized them using WordCloud tool. By conducting a questionnaire on these videos, subjective evaluations were obtained by SD method. Comparing the results obtained by machine learning with the results from the questionnaire, this study verifies the validity of the review evaluation using tf-idf method.