| Abstract: |
This study reviews the recent literature on Automated Emotion Recognition
(AER), focusing on image and video-based methods applied in marketing
research. The literature overview highlights the transformative potential of
AER, including real-time, unobtrusive, and scalable applications. It
identifies key tools, including Noldus' FaceReader and iMotions' Facial
Expression Analysis, as significant contributors to insights in diverse
contexts such as e-commerce, social media, and online platforms. The analysis
also addresses theoretical challenges, such as the limitations of Ekman's
basic emotion theory and the contextual dependence of facial expressions.
Practical recommendations for AER use include incorporating multimodal
approaches and ensuring cultural and contextual inclusivity in training
datasets. Thus, the current work advances the discourse on leveraging AER for
refined marketing strategies. |