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计算机系统应用英文版:2019,28(1):69-74

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基于聚类的网络直播群体行为建模分析

兰荣亨¹, 朱格², 杨文², 田野², 朱明¹

(1.中国科学技术大学信息科学技术学院, 合肥 230027;2.中国科学技术大学计算机科学与技术学院, 合肥 230027)

Modeling and Analysis of Community Behavior on Live Streaming Platform Using Clustering Approach

LAN Rong-Heng¹, ZHU Ge², YANG Wen², TIAN Ye², ZHU Ming¹

(1.School of Information Science and Technology, University of Science and Technology of China, Hefei 230027, China;2.School of Computer Science and Technology, University of Science and Technology of China, Hefei 230027, China)

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本文已被：浏览 2119次下载 2040次
Received:July 03, 2018 Revised:August 13, 2018

中文摘要: 近年来，随着互联网技术的不断发展，以及手机、平板电脑等移动终端的普及，网络直播逐渐兴起并壮大.国内众多直播平台基本都有送礼机制，允许观众购买平台提供的虚拟礼物来打赏主播.观众的打赏对于主播和平台来说都是主要的收入来源之一，所以理解观众的行为以挖掘观众的用户价值，提升用户的变现能力就显得尤为重要.本文以斗鱼直播平台为例，聚焦于直播平台上的高消费群体，通过构建观众特征，采用聚类方法分析高消费群体的行为.实验结果表明，高消费观众可被分为特征有明显差异的三类群体.对这三类观众的特征，本文进一步进行详细分析，为直播平台面向用户的差异化产品服务提供依据.

中文关键词: 网络直播用户行为特征挖掘聚类分析数据挖掘

Abstract:With the continuous development of Internet technology, and the popularization of mobile phones, computer tablets, and other mobile terminals, live video streaming has flourished and expanded over the past few years. Almost every live video streaming platform in China has virtual-gifts donating mechanism, which allows viewers to buy virtual-gifts provided by the platform for rewarding the broadcasters. Viewers' virtual-gifts donation is one of the most important sources of revenue for both the broadcaster and the platform, which makes it important to understand the viewer's behavior, so that it can be used to explore user's value and enhance user's liquidity. In this study, we take Douyu live video streaming platform as a case study, mainly focusing on the high consumption community on the platform. We specifically construct viewer features to analyze their behavior through clustering approach. The experiment result shows that the high consumption community can be divided into three clusters with significant difference in their behavior. We also conduct detailed analysis regarding viewer characteristics for all these three clusters, and offer suggestions for the platform to provide diversified user-oriented services.

keywords: live video broadcasting user behaviors feature mining clustering analysis data mining

文章编号： 中图分类号： 文献标志码：

基金项目:国家自然科学基金（61672486）；国家科技重大专项（2017ZX03001019-004）；安徽省自然科学基金（1608085MF126）

引用文本：
兰荣亨,朱格,杨文,田野,朱明.基于聚类的网络直播群体行为建模分析.计算机系统应用,2019,28(1):69-74
LAN Rong-Heng,ZHU Ge,YANG Wen,TIAN Ye,ZHU Ming.Modeling and Analysis of Community Behavior on Live Streaming Platform Using Clustering Approach.COMPUTER SYSTEMS APPLICATIONS,2019,28(1):69-74

Author Name	Affiliation	E-mail
LAN Rong-Heng	School of Information Science and Technology, University of Science and Technology of China, Hefei 230027, China
ZHU Ge	School of Computer Science and Technology, University of Science and Technology of China, Hefei 230027, China
YANG Wen	School of Computer Science and Technology, University of Science and Technology of China, Hefei 230027, China
TIAN Ye	School of Computer Science and Technology, University of Science and Technology of China, Hefei 230027, China	yetian@ustc.edu.cn
ZHU Ming	School of Information Science and Technology, University of Science and Technology of China, Hefei 230027, China