基于聚类的网络直播群体行为建模分析
作者:
作者单位:

作者简介:

通讯作者:

中图分类号:

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)


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

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 增强出版
  • |
  • 文章评论
    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.

    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.

    参考文献
    相似文献
    引证文献
引用本文

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

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:2018-07-03
  • 最后修改日期:2018-08-13
  • 录用日期:
  • 在线发布日期: 2018-12-27
  • 出版日期:
您是第位访问者
版权所有:中国科学院软件研究所 京ICP备05046678号-3
地址:北京海淀区中关村南四街4号 中科院软件园区 7号楼305房间,邮政编码:100190
电话:010-62661041 传真: Email:csa (a) iscas.ac.cn
技术支持:北京勤云科技发展有限公司

京公网安备 11040202500063号