摘要
弹幕视频深受用户青睐,探讨弹幕视频播放量的影响因素及组合效应有利于提高弹幕视频播放服务和优化播放行为。文章以ELM为理论框架构建弹幕视频播放量影响因素模型,通过抓取哔哩哔哩弹幕网视频数据,综合采用层次回归和fsQCA方法对模型进行验证。层次回归结果表明:中心路径中的4个变量(点赞数、弹幕数、评论数和转发数)均对弹幕视频播放量产生正向显著影响;边缘路径中的视频作者粉丝数和投稿数分别对弹幕视频播放量产生显著的正向和负向影响;fsQCA的结果识别出2条引发弹幕视频播放的组态路径。
Bullet-screen videos are well favored by users. Investigating the influencing factors and the configuration effect of the view counts is very helpful to improve the streaming services of bullet-screen videos and to optimize the streaming behavior. Drawing on the Elaboration Likelihood Model(ELM),this paper develops an influencing factor model of bullet-screen video streaming. Fetching data from Bilibili, a bullet-screen video platform,it verifies the model by means of hierarchical regression and fsQCA. The results of hierarchical regression analysis show that the variables(likes, bullet-comments, comments and forwards) in the central path are positive correlated with the view counts of the videos;creators’ followers and the videos posted by creators in peripheral path have significant positive and negative effect on the view counts respectively. fsQCA analysis identifies two configuration paths which trigger the streaming of bullet screen videos.
作者
陈明红
黄嘉乐
方世深
黄涵慧
CHEN Minghong;HUANG Jiale;FANG Shishen;HUANG Hanhui
出处
《图书馆论坛》
CSSCI
北大核心
2022年第6期150-160,F0003,共12页
Library Tribune
基金
国家自然科学基金项目“基于HSM的移动互联网用户信息搜索行为研究”(项目编号:71603295)
广东省自然科学基金项目“大数据信息资源云建设与深度挖掘研究”(项目编号:2016A030313334)研究成果。
