Fiona Chew, professor of television, radio and film, and Beth Egan, associate professor of advertising, worked on a paper that won first place in the Open Paper Competition for the Broadcast Education Association (BEA) Research Division this year. The paper was co-authored by Egan and Chew with Chilukuri K. Mohan, Sanup Araballi, Dongqing Xu and Amanda Qi Ni.
The paper, “Developing an ad viewing retention model for TV comedy through machine learning,” will be presented at the virtual annual conference in April. This paper presents a model for audience prediction which can potentially be used to predict audience retention at various levels of ad clutter allowing networks to curate commercial breaks to optimize the viewer experience.
This is Chew and Egan’s second BEA win with a paper they worked on together. In 2019, their paper “TV Program-Ad Genre Congruence and Ad Avoidance: Applying Neural Networks to Assess Effects” took top place in the BEA’s research division.
This research was funded by a CUSE Grant and is an interdisciplinary collaboration between the Newhouse School and the College of Engineering and Computer Science, with data provided by Comscore.