``Automated Coding of Political Campaign Advertisement Videos: An Empirical Validation Study.''

 

  Abstract

Television advertisements play an essential role in modern political campaigns with several billion dollars spent in the 2018 general election alone. For over two decades, researchers have studied TV ads by analyzing the hand-coded data from the Wisconsin Advertising Project (WAP) 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 at least as accurate as human coding for many variables of the WAP/WMP data sets. Since many candidates make their advertisement videos available on the Internet, automated coding can dramatically improve the efficiency and scope of campaign advertisement research. (Last Revised, April 2019)

© Kosuke Imai
 Last modified: Wed Apr 24 21:32:46 EDT 2019