Understanding Consumer Advertising via Audio Analytics of Sports Videos
Stuart John Barnes, Weisha Wang · 2023
This research develops and applies a research process integrating advanced data analytics methods, including machine learning, to test a research model for a number of existing and new theoretical relationships between voice, music, and content features and net positive affect from sports video advertisements. This research uses YouTube video data from the most frequently advertised products and brands in Super Bowls from 2000 to 2020. The findings outline the most effective audio and music features which will have a greater impact on net positive affect. The results have methodological and theoretical implications and consequences for practitioners aiming to develop the most affective advertisements for viewers.