Star Business Value Prediction based on Sentiment Analysis

Meixuan Li

doi:10.54691/bcpbm.v13i.87

Authors

Meixuan Li

DOI:

https://doi.org/10.54691/bcpbm.v13i.87

Keywords:

Youtube Comments; Crawlers; Sentiment Analysis; Word2vec; LSTM.

Abstract

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.

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