Automated Coding of Political Campaign Advertisement Videos: An Empirical Validation Study
Automated Coding of Political Campaign Advertisement Videos: An Empirical Validation Study
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DOI：
10.1017/pan.2022.26
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发表时间：
2022-11
影响因子：
5.4
通讯作者：
Alexander Tarr;June Hwang;K. Imai
中科院分区：
文献类型：
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作者：
Alexander Tarr;June Hwang;K. Imai
摘要视频广告，无论是通过电视还是互联网，在现代政治运动中发挥着重要作用。二十多年来，研究人员一直通过分析来自威斯康星州广告项目及其继任者卫斯理媒体项目（Wesleyan Media Project，WMP）的手工编码数据来研究电视视频广告。不幸的是，手动编码超过一百个变量，如问题提到，对手的外观和消极，对于许多视频是一个费力和昂贵的过程。我们建议自动编码活动广告视频。应用最先进的机器学习方法，我们从每个视频文件中提取各种音频和图像特征。我们表明，我们的机器编码是人类编码的许多变量的WMP数据集。由于许多候选人在互联网上提供他们的广告视频，自动编码可以大大提高竞选广告研究的效率和范围。开放源码软件包可用于实施所提出的方法。
Abstract Video advertisements, either through television or the Internet, play an essential role in modern political campaigns. For over two decades, researchers have studied television video ads by analyzing the hand-coded data from the Wisconsin Advertising Project and its successor, the Wesleyan Media Project (WMP). Unfortunately, manually coding more than a hundred of variables, such as issue mentions, opponent appearance, and negativity, for many videos is a laborious and expensive process. We propose to automatically code campaign advertisement videos. Applying state-of-the-art machine learning methods, we extract various audio and image features from each video file. We show that our machine coding is comparable to human coding for many variables of the WMP datasets. Since many candidates make their advertisement videos available on the Internet, automated coding can dramatically improve the efficiency and scope of campaign advertisement research. Open-source software package is available for implementing the proposed methodology.