网络直播平台数据挖掘与行为分析综述

随着移动通信和互联网技术的不断发展,网络直播逐渐成为了新媒体环境下人们青睐的在线娱乐和信息传播方式.目前广泛应用于课堂教学、真人秀、电竞赛事、品牌营销等方面.数百万主播与数亿计观众的活跃加入和互动,产生了丰富的在线人群行为活动数据,为开展大规模人群行为动力学、平台内容推荐与检测、在线社群演化等研究提供了丰富的实验场景.本文通过梳理国内外网络直播平台数据挖掘与行为分析的相关研究文献,分析了直播平台负载水平、观众行为、主播行为以及社群网络的特征和变化规律,并对直播平台中大规模人群行为表现出的时空规律和重尾效应进行了总结.直播平台中各种社群网络的形成和演化机制、内容推荐与检测等是未来网络直播领域研究的发展趋势.

Live streaming: Data mining and behavior analysis

With the rapid development of mobile communication and Internet technologies, online live streaming has gradually become popular for information communication and entertainment in the new media environment.Live streaming has been widely used in teaching, reality show, E-sports games and events, brand marketing and other aspects. With the active participation of millions of streamers and hundreds of millions of viewers,massive online crowd behavior activity data are generated, which offers rich experimental scenarios for largescale crowd behavior dynamics research, live streaming channel recommendation and online community evolution. In this paper, we summarize the relevant research literature of live streaming, and review current studies from a comprehensive list of aspects: workload pattern, viewers and streamers behavior, community network discovery and analysis, etc. We summarize the temporal and spatial patterns of live streaming platform workload, heavy tailed effect of large-scale crowd behavior in live streaming platform, etc. We believe that the future work on live streaming can be directed in the examination of formation and evolution mechanism of various community networks formed by large-scale users, as well as the recommendation and detection of live streaming content.