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Automated emotion recognition in marketing research: A systematic literature review of current image and video-based methods

Author

Listed:
  • Laura Daniela Bohorquez Camacho

  • Marcel Lichters

  • Pedro J. Amor

    (Faculty of Economics and Management, Otto-von-Guericke University Magdeburg)

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.

Suggested Citation

  • Laura Daniela Bohorquez Camacho & Marcel Lichters & Pedro J. Amor, 2025. "Automated emotion recognition in marketing research: A systematic literature review of current image and video-based methods," FEMM Working Papers 25002, Otto-von-Guericke University Magdeburg, Faculty of Economics and Management.
    • Handle: RePEc:mag:wpaper:25002
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    File URL: https://www.fww.ovgu.de/fww_media/femm/femm_2025/2025_02.pdf
    File Function: First version, 2011
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    JEL classification:

    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing
    • M37 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Advertising

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