Open AccessResearch on Prediction of Different Categories of Video based on YOUTUBE Using Text Mining and Sentiment Analysis
Author(s) -
Gao Lin
Publication year - 2021
Publication title -
bcp business and management
Language(s) - English
Resource type - Journals
ISSN - 2692-6156
DOI - 10.54691/bcpbm.v13i.91
Subject(s) - sentiment analysis , social media , public opinion , quality (philosophy) , content analysis , computer science , product (mathematics) , value (mathematics) , psychology , data science , world wide web , sociology , political science , social science , artificial intelligence , epistemology , philosophy , geometry , mathematics , machine learning , politics , law
With the development of online commentary research, scholars have tried to tap into the deeper value of online commentary from the analysis of sentiment analysis, quality evaluation, false comment recognition to the usefulness of comments. Previous studies have focused on online product reviews while news reviews. Social media research has been relatively rare. social media and news commentary contain readers' opinions and evaluations on current events, and reflect the trend of public opinion. The purpose of this paper is to investigate and analyze the intrinsic link between social media content of different type and the number of commentaries, and sentiment analysis.