Hongjun Lim

Kootenay Association for Science & Technology

Papers

Total Citations

H-Index

About

Hongjun Lim is a researcher at the forefront of affective computing and natural language processing, with a focused expertise in multiclass emotion detection from text. His most cited work, "Detecting Multiclass Emotions from Labeled Movie Scripts" (2018), tackles a critical challenge in AI: moving beyond binary sentiment analysis to precisely discern nuanced negative emotions like anger and sadness. This contribution is vital for developing empathetic AI systems capable of delicate, context-aware responses. With 5 citations, this paper has laid groundwork for more sophisticated emotion-aware technologies. Lim’s research addresses a key limitation in existing sentiment tools, which often oversimplify human emotional complexity. His work is particularly notable for its application to movie scripts—a rich, naturalistic data source—demonstrating a creative approach to training models on authentic emotional expressions. By advancing the granularity of emotion detection, Hongjun Lim is helping to shape the future of human-AI interaction, where machines can better understand and respond to the full spectrum of human feelings.