Affective Computing Research Progress and Its Implications for Education Technology: A Bibliometric Analysis Based on Web of Science via VOSviewer
- DOI
- 10.2991/978-94-6463-242-2_53How to use a DOI?
- Keywords
- Emotion Recognition; Physiological Signal; Deep Learning; Electroencephalography
- Abstract
Affective Computing (AC) is a dynamic and evolving research field. This paper presents a bibliometric analysis of 1428 publications related to affective computing, extracted from the Web of Science database, using the VOSviewer software. Through an examination of the existing literature, the study investigates the quantity of AC publications, research countries, important institutions, and leading authors. Co-citation analysis reveals that IEEE Transactions on Affective Computing is the most influential source of literature. Keyword co-occurrence and clustering analysis identify five main research directions in AC: emotion recognition, physiological signal, human-computer interaction, deep learning, and electroencephalography. Lastly, the paper provides relevant recommendations for AC research in educational technology, focusing on personalized learning experiences, affective feedback, emotion recognition, and affective robots.
- Copyright
- © 2024 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Qingbo Jiang AU - Yong Huang PY - 2023 DA - 2023/09/22 TI - Affective Computing Research Progress and Its Implications for Education Technology: A Bibliometric Analysis Based on Web of Science via VOSviewer BT - Proceedings of the 2023 4th International Conference on Artificial Intelligence and Education (ICAIE 2023) PB - Atlantis Press SP - 425 EP - 437 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-242-2_53 DO - 10.2991/978-94-6463-242-2_53 ID - Jiang2023 ER -