Affective Computing: Recent Advances, Challenges, and Future Trends

Abstract

Affective computing is a rapidly growing multidisciplinary field that encompasses computer science, engineering, psychology, neuroscience, and other related disciplines. Although the literature in this field has progressively grown and matured, the lack of a comprehensive bibliometric analysis limits the overall understanding of the theory, technical methods, and applications of affective computing. This review presents a quantitative analysis of 33,448 articles published in the period from 1997 to 2023, identifying challenges, calling attention to 10 technology trends, and outlining a blueprint for future applications. The findings reveal that the emerging forces represented by China and India are transforming the global research landscape in affective computing, injecting transformative power and fostering extensive collaborations, while emphasizing the need for more consensus regarding standard setting and ethical norms. The 5 core research themes identified via cluster analysis not only represent key areas of international interest but also indicate new research frontiers. Important trends in affective computing include the establishment of large-scale datasets, the use of both data and knowledge to drive innovation, fine-grained sentiment classification, and multimodal fusion, among others. Amid rapid iteration and technology upgrades, affective computing has great application prospects in fields such as brain–computer interfaces, empathic human–computer dialogue, assisted decision-making, and virtual reality.