%0 Journal Article
%T 融媒体环境下视听传播效果评估的指标体系建构 ——基于VAR模型的大数据计算及分析<br>Construction of Evaluation Index System of Audio-visual Communication Effects Measurement System in the Era of Media Convergence: Big Data Mining Based on VAR Model
%A 周勇
%A 赵璇
%J 国际新闻界
%D 2017
%X 摘要 媒介融合环境的深刻变化使视听信息传播面临着由传统电视向包括电视、电脑和手机等移动终端在内的多屏互动模式的转变。在这种转变过程中所积累的以互联网为主要来源的大数据将彻底改变长期以来为各方接受的电视收视率调查方法。本文通过理论梳理将传统收视率、时移收视、网络点击量、网络舆情等多个维度纳入考察范围，建立了视听信息传播效果评估指标体系。然后以10部电视剧的数据为例，引入向量自回归模型（VAR）分析了在时间维度上各指标之间的关系，确定了指标体系的权重，并对初始指标体系模型进行了修正。研究发现，网络搜索指数和微话题热度对收视率在短期内有明显的带动作用，而媒体转载量和网络正面评论的比例对于收视率提升的长期影响则更为明显。<br>Media convergence changes media environment profoundly, which makes the transmission of audio-visual information change from single channel -- traditional television -- to the multiscreen interactive mode, including television, computer and mobile terminals. The big data, which mostly comes from internet, accumulating in this process of change, will completely change the traditional TV rating survey method which accepted by all parties for a long time. This study intends to establish an audio-visual communication effects measurement system by integrating measurement systems such as audience ratings, time-shift, internet clickstreams, and social media opinion mining. Using the data from ten television series, this study uses Vector Autoregressive model （VAR（ to analyze the relationships between various existing measurement systems, which is further used to determine the weights of different measurement indexes. The results suggest that the Baidu search index and the trending topics on Weibo have significant effects on the ratings in the short term, and the quantity of media coverage and the positive word-of-mouth on social media contribute to the long term success measured in the ratings
%K 视听传播
%K 传播效果
%K 大数据
%K 指标体系
%K VAR模型<br>audio-visual communication
%K media effects
%K big data
%K measurement system
%K VAR model
%U http://cjjc.ruc.edu.cn/CN/abstract/abstract715.shtml