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.