Tone Classification for Political Advertising Video using Multimodal Cues


Politics has always gotten much attention throughout history, and video advertisement has become one of the most essential tools for political communication. Analysis of such political advertising videos can provide more insight into the political campaign by evaluating the message in it, such as a candidate’s attitude toward a certain political issue. In this paper, we propose to classify the tone in political advertising videos into promotive, contrastive, and their mixture using a deep neural network to benefit automatic analysis of such videos. We especially explore how different modalities of videos, i.e., visuals, audio, and text, contribute to improving the classification accuracy.

Proceedings of the 3rd ACM Workshop on Intelligent Cross-Data Analysis and Retrieval
Yuta Nakashima
Yuta Nakashima

Yuta Nakashima is a professor with Institute for Datability Science, Osaka University. His research interests include computer vision, pattern recognition, natural langauge processing, and their applications.