摘要
本文从节目微场景的角度重新定义和分解广播电视节目的标签化特征,并以微场景为沟通桥梁,进行广播电视节目与互联网社交平台多维数据的精准匹配与关联分析,研究节目微场景的深度挖掘技术和微场景与多维数据进行关联分析方法,有助于广播电视内容制作方提供更精细化的内容服务、提升用户粘性,有助于广播电视节目适应日益发展的互联网传播环境,提升广播电视传播影响力与舆论引导力,推动传统媒体和新兴媒体的深度融合。
In this paper,label characteristics of radio and TV programs are redefined and decomposed from the perspective of program microscene,and accurate matching and correlation analysis of multi-dimensional data between radio and TV programs and Internet social platforms are conducted by using micro-scenes as communication bridge.In addition,this paper studies deep mining technology of program microscene and correlation analysis method between micro-scene and multi-dimensional data,It will help content producers to provide more refined services thus enhancing user stickiness,help radio and television programs adapt to growing Internet communication environment,enhanc the influence of radio and television communication and public opinion guidance,and promot deep convergence of traditional media and emerging media.
作者
徐杰
何晶
施玉海
张伟
Xu Jie;He Jing;Shi Yuhai;Zhang Wei(Academy of Broadcasting Science,NRTA,Beijing 100866,China)
出处
《广播与电视技术》
2021年第3期25-29,共5页
Radio & TV Broadcast Engineering
基金
广播电视科学研究院2020年基本科研项目支持,项目编号:JBKY2019031
关键词
传播影响力
微场景
标签化
内容画像
舆情分析
Communication influence
Micro-scene
Labeling
Content portrait
Public opinion analysis