Application of K-means clustering algorithm in the analysis of college students' online entertainment consumption

Abstract

It is benefit for college students to explore the characteristics of online entertainment consumption and give them appropriate guidance. The Online entertainment consumption of some undergraduate students is investigated in this paper, and the K-means algorithm is used in the survey to carry out clustering analysis. The results show that in terms of online entertainment consumer behaviour, the consumption amount is polarized, consumption is gender-differentiated, consumer contents are diversified, consumer has more copyrighted-awareness., etc. From the clustering results, the K-means algorithm is more effective for analyzing the characteristics of online entertainment consumption behavior.