Open AccessStar Business Value Prediction based on Sentiment Analysis
Author(s) -
Meixuan Li
Publication year - 2021
Publication title -
bcp business and management
Language(s) - English
Resource type - Journals
ISSN - 2692-6156
DOI - 10.54691/bcpbm.v13i.87
Subject(s) - word2vec , popularity , computer science , sentiment analysis , web crawler , entertainment , word (group theory) , value (mathematics) , work (physics) , content (measure theory) , artificial intelligence , world wide web , information retrieval , machine learning , engineering , mathematics , psychology , mechanical engineering , social psychology , art , mathematical analysis , embedding , visual arts , geometry
The article crawls the audience comments from some videos on the YouTube platform of "Talk Show Conference Season 3", extracts relevant content about popular champions Wang Mian and Wang Jianguo for sentiment analysis, uses Google Data API to design a crawler to obtain comment content, and to crawl After the received content is preprocessed, Word2vec is used to build a word vector model, and finally an LSTM model is built for training prediction. It can be seen that the popularity of the player Wang Mian is higher than that of Wang Jianguo. The entertainment company where the two are located can adjust the artist's work according to the changes in the public's love for the players.