Jia-Hua Jeng is a PhD candidate in WP2 Computational Social Science at
MediaFutures and DARS research group. He received two master’s degrees from
King’s College London in MSc Data Science and National Taichung University of
Education in MSc Digital Content Technology, mainly for AI, Data Mining, Machine
Learning, Big Data, Data Analytics, Internet Marketing and Learning Science. 

His research interests are Recommender Systems, Data Science, and User Modelling in news media.

Book anthology

• Jia-Hua Jeng (2024). Bridging Viewpoints in News with Recommender Systems. (external link)

Academic book chapter

• Jia-Hua Jeng; Gloria Anne Babile Kasangu; Alain Dominique Starke et al. (2024). Emotional Reframing of Economic News using a Large Language Model. (external link)
• Jia-Hua Jeng; Alain Dominique Starke; Christoph Trattner (2023). Towards Attitudinal Change in News Recommender Systems: A Pilot Study on Climate Change. (external link)
• Jia-Hua Jeng; Gloria Anne Babile Kasangu; Alain Dominique Starke et al. (2025). The role of GPT as an adaptive technology in climate change journalism. (external link)

Academic article

• Jia-Hua Jeng; Gloria Anne Babile Kasangu; Alain Dominique Starke et al. (2024). Negativity Sells? Using an LLM to Affectively Reframe News Articles in a Recommender System. (external link)
• Jørgen Eknes-Riple; Jia-Hua Jeng; Alain Dominique Starke et al. (2025). Hope, Fear, or Anger? How Emotional Framing in a News Recommender System Guides User Preferences. (external link)

See a complete overview of publications in Cristin.