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Vis Inf
Vis Inf  2020, Vol. 4 Issue (3): 1-11    DOI: 10.1016/j.visinf.2020.06.001
论文     
TVseer：一个电视收视率的可视分析系统
Xiaoyan Kui, Huihao Lv, Zhengliang Tang, Haowen Zhou, Wang Yang, Jinqiu Li,Jialin Guo, Jiazhi Xia
Central South University, China
TVseer: A visual analytics system for television ratings
Xiaoyan Kui, Huihao Lv, Zhengliang Tang, Haowen Zhou, Wang Yang, Jinqiu Li,Jialin Guo, Jiazhi Xia
Central South University, China
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摘要： 电视收视率作为电视节目受欢迎程度的重要指标，一直是电视台关注的重点。尤其是近年来各种网络媒体的兴起，导致电视台之间的竞争越来越激烈。各大电视台想要提升竞争力，需要对收视率进行有效的分析。对收视率的有效分析可以帮助发现影响节目收视率变化的原因，从而指导电视台工作者进行更好的节目制作和节目编排。可视分析方法利用多视图展示数据的不同角度，使用交互功能帮助用户探索数据。通过多视图之间的联动，用户可以方便地观察分析电视台，电视节目，观众行为之间的关联关系。交互式探索可以将人的知识增加到分析过程当中，有助于发现影响收视率的关键因素，了解不同电视节目收视率之间的潜在联系。 （1）相关性分析模型 我们利用相关性计算帮助用户发现可能存在竞争关系的电视节目。节目间的竞争关系如下：如果两个播放时间有重叠的电视节目的收视人数随时间变化序列呈现负相关，那么我们认为这两个电视节目存在竞争关系。我们选择了Spearman相关系数计算收视率序列的相关性，因为它更专注于数据的趋势。 （2）聚类模型 通过对观众观看电视序列数据的分析，我们总结了四个特征以描述观众行为：对电视台的偏爱、对电视节目类型的偏爱、对观看时间段的偏爱、平均观看时间。观众的分组通过对每个特征分别进行聚类分析实现。
关键词： 电视频域可视化;  收视率分析;  时序数据;  可视分析    
Abstract: The television ratings provide an effective way to analyze the popularity of TV programs and audiences’ watching habits. Most previous studies have analyzed the ratings from a single perspective. Few efforts have integrated analysis from different perspectives and explored the reasons for changes in ratings. In this paper, we design a visual analysis system called TVseer to analyze audience ratings from three perspectives: TV channels, TV programs, and audiences. The system can help users explore the factors that affect ratings, and assist them in decisions about program productions and schedules. There are six linked views in TVseer: the channel ratings view and program ratings view show ratings change information from the perspective of TV channels and programs respectively; the overlapping program competition view and the same-type program competition view indicate the competitive relationships among programs; the audience transfer view shows how audiences are moving among different channels; the audience group view displays audience groups based on their watching behavior. Besides, we also construct case studies and expert interviews to prove our system is useful and effective.
Key words: Visualization in television    Ratings analysis    Time series data    Visual analytics
出版日期: 2020-06-19
通讯作者: Jiazhi Xia     E-mail: xiajiazhi@csu.edu.cn
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Xiaoyan Kui
Huihao Lv
Zhengliang Tang
Haowen Zhou
Wang Yang
Jinqiu Li
Jialin Guo
Jiazhi Xia

引用本文:

Xiaoyan Kui, Huihao Lv, Zhengliang Tang, Haowen Zhou, Wang Yang, Jinqiu Li, Jialin Guo, Jiazhi Xia. TVseer: A visual analytics system for television ratings. Vis Inf, 2020, 4(3): 1-11.

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http://www.zjujournals.com/vi/CN/10.1016/j.visinf.2020.06.001    或    http://www.zjujournals.com/vi/CN/Y2020/V4/I3/1

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