A Study On The User Comment Rules Based On The Comment Data Of Network Variety Shows Of Bilibili

With the rapid development of the Internet and the rise of Web2.0 technology,the number of Internet users has increased sharply.Internet users are no longer satisfied with being passive receivers of network information,but gradually start to generate and publish words by themselves.Now it has become a new trend.Online comments are an important presentation of this new trend.A large number of Internet users on the website of comment most directly reflects the users of products,services or content directly,in the network users comment have a lot of feedback,the website also records the user's various related data information,the information both standardized structured information,such as the user's age,grade,gender,comment time,etc.,also have a lot of unstructured information,mostly exists in the comment text,is the original content of network users,fully reflects the network user's attitudes,preferences,feelings,opinions,etc.Compared with general e-commerce products,online variety shows have higher degree and longer time of user engagement.As a result,users will be more inclined to post more realistic feeling in the comments section below to share with relevant fans throughout the viewing.Therefore,summarizing the feature of the network user's commentary rules,emotional tendency and preferences from digging into and analyzing users comments has great meaning to the network platform construction and the program content improvement.This paper aims to use the way of “data visualizations” to dig out the user comments rules in the Korean variety show "Running Man" on the B-station platform.In this study,through the crawler program to collect all the comments information and extracting 10 indicators from data processing.Through correlation analysis of indicators,carrying out data visualization analysis on indicators with certain correlation and distribution rules of each index.Verifying the correlation between indicators and analyzing the distribution of indicators at the same time.Then extracting keywords from comment text to explore the popularity and the relationship among the star host members and find out the explanation.At last,analyzing the word frequency and word cloud generation of the whole comment briefly to display the summary information graphically.In conclusion,through the research and analysis of the regulation of "Running Man" program network comments,trying to tease the commentary behavior rules of the program and the relationship between the host members and then make some relevant suggestions.