Fusion of Artificial Intelligence and Social Media Consumer Neuroscience
(A2021-104124)

AUTHORS

Jing Zhang, Kookmin University; Eun-Ju Lee, Sungkyunkwan University

ABSTRACT

In contrast with traditional advertising (e.g., TV, radio), effective social media advertising engages consumers and inspires them to take part in subsequent activities, leading to further consumption or deeper loyalty to a brand. Our research (Study 1) used cutting-edge, interdisciplinary neuromarketing methods to collect behavioral and neural data related to consumer engagement. In study 2, we performed deep learning techniques in analyzing the collected neural data (Study 2). We employed classic machine learning for classification and prediction and used the latest deep learning techniques (e.g., CNN, GAN) to build new mathematical models. We compared these multiple models to determine a more effective classification scheme for consumers in terms of their engagement. This attempt to combine neuromarketing with deep learning research in the academic business domain provides the necessary foundation for future commercial rollouts. Keywords: deep learning, neuromarketing, consumer engagement, social media advertising, consumption