Influence of Consumers’ Temporary Affect on Ad Engagement: A Computational Research Approach

Abstract

This study examined the influence of consumers’ temporary affective states during ad exposure on their engagement with different types of ads that are categorized based on theoretically derived attention-grabbing characteristics. A computational research approach was used, cross-analyzing proxy measures of real-time affective fluctuation of viewers during the 2019 Super Bowl broadcast and their tweets regarding the ads aired during the Super Bowl. The results demonstrated significant impact of consumers’ temporary affective states, induced by the performance of the team they cheer for, on their engagement with different types of ads, even when they were exposed to the same set of ads during commercial breaks. Specifically, consumers in the positive affective state showed greater tendency to be drawn to engage with high semantic-affinity ads than those in the negative affective state. Consumers in the negative affective state showed greater tendency to be drawn to engage with more positively valenced ads than those in the positive affective state. This study provides theoretical contributions regarding the role of consumers’ affect in their engagement with ads and practical implications for ad targeting and ad placement strategies based on consumers’ temporary affect.

Acknowledgments

The authors would like to thank Maral Abdollahi, doctoral student at Hubbard School of Journalism and Mass Communication, University of Minnesota, Twin Cities, for her help with manual annotation needed in the deep-learning approach.

Additional information

Funding

This work was supported by the Ralph D. Casey Dissertation Research Award given by the Hubbard School of Journalism and Mass Communication, University of Minnesota.

Notes on contributors

Xinyu Lu

Xinyu Lu (PhD, University of Minnesota) is an assistant professor, School of Journalism and Communication, Shanghai International Studies University.

Debarati Das

Debarati Das (BE, PES University) is a doctoral student, Department of Computer Science and Engineering, University of Minnesota.

Jisu Huh

Jisu Huh (PhD, University of Georgia) is a professor, Hubbard School of Journalism and Mass Communication, University of Minnesota.

Jaideep Srivastava

Jaideep Srivastava (PhD, University of California, Berkeley) is a professor, Department of Computer Science and Engineering, University of Minnesota.