Facial and speech markers of emotions in Super Bowl advertisements: A registered report

Abstract

This dissertation explores the emotional dynamics of advertising, focusing on Super Bowl commercials aimed from 2020 to 2023. It utilizes advanced technology, hume.ai, to analyze the emotional dimensions of these commercials. The primary aim is to understand how emotional content in Super Bowl advertisements influences viewer preferences, as reflected in the USA Today Ad Meter rankings. The emotional analysis covers four channels: Facial Expression, Speech Prosody, Vocal Burst, and Emotional Language. Facial Expression reveals 28 dimensions, generating 48 outputs. Speech Prosody uncovers 18 dimensions with 48 outputs. Vocal Burst identifies 24 dimensions, also with 48 outputs, while Emotional Language explores 53 dimensions. Data analysis involves studying moment-to-moment emotional reactions to advertisements, considering language, prosody, burst, and facial expressions. Implications extend to academia, offering improved measurement accuracy and real-time emotional contagion assessment. For advertisers, it enhances advertisement impact understanding, optimizes content, and refines advertising strategies. In conclusion, this dissertation combines Ad Meter rankings with hume.ai to decode the emotional content of Super Bowl advertisements. It promises to enhance emotional measurement precision in advertising, improving advertising campaigns, and fostering academia-industry collaboration.