Across cultures and centuries, emotions have been expressed, encoded, and preserved in both texts and images. Recent advances in affective computing now offer new opportunities to study these emotional traces at scale. This talk examines how computational approaches to emotion—from early dictionary- and rule-based techniques to contemporary deep learning and large language models—have expanded the analytical possibilities for historical research. Applications in historical psychology will be discussed, demonstrating how AI-driven analysis of premodern texts and historical images can illuminate long-term patterns in collective emotions and cultural mindsets. By integrating computational methods with humanistic interpretation, the talk considers both the potential and the limitations of using artificial intelligence to reconstruct aspects of emotional life in the past.
Yuqi Chen is an Assistant Professor jointly appointed at the Hong Kong Institute for the Humanities and Social Sciences and the Faculty of Arts, The University of Hong Kong. She received both her B.A. and Ph.D. degrees from Peking University and was a visiting scholar at the Institute for Quantitative Social Science at Harvard University. She is actively engaged in the fields of Quantitative History and Digital Humanities. Her research focuses on integrating AI and computational methods with humanities research, aiming to uncover new insights through innovative interdisciplinary approaches.
This series aims to introduce a wide range of cutting-edge research in various disciplines and areas. If you have any questions about the Interdisciplinary Research Seminar or would like to be removed from this mailing list, please contact Professor Ghassan Moazzin (gmoazzin@hku.hk).