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Mr James Boyce

j.boyce@business.uq.edu.au

Publications

Journal Article (1)
Conference Papers (5)

Journal Article

Burton-Jones, Andrew, Amano, Tatsuya, Boyce, James, Chau, Patrick, Feng, Juan (Jane), Guzman, Indira R., Jarvenpaa, Sirkka, Li, Jingqi (Celeste), Namvar, Morteza, Padmanabhan, Balaji, Pineda, Jose, Richet, Jean-Loup, Sarker, Suprateek, Seidel, Stefan, Sharma, Sujeet, Vogel, Doug, Wang, Harry and Yoon, Victoria (2025). This article is not just in English: making science more inclusive and impactful with artificial intelligence translation. Australasian Journal of Information Systems, 29 5875, 1-54. doi: 10.3127/ajis.v29.5875

Conference Papers

Boyce, James, Phan, Thuy Linh (Isabella), Namvar, Morteza, Akhlaghpour, Saeed and Risius, Marten (2025). Who nudges the nudger? Conceptualizing an LLM-based Reciprocal Nudging System (LRNS). Pacific Asia Conference on Information Systems: PACIS 2025, Kuala Lumpur, Malaysia, 5 - 9 July 2025. Atlanta, GA, United States: Association for Information Systems (AIS).
Boyce, James, Namvar, Morteza, Lyu, Beibei, Liu, Yiying, Mensforth, Martha and Tao, Hsi-Wen (2025). The Interplay of Heuristic and Systematic Processing of Information in News Validation: A Natural Language Processing Approach. 58th Hawaii International Conference on System Sciences, Hi, Jan 07-10, 2025. Honolulu: IEEE Computer Society.
Boyce, James (2024). The Matrix of Influence: Generative AI Digital Nudging Leveraging Generative AI to Transform Digital Nudging. Association for Information Systems.
Namvar, Morteza, Akhlaghpour, Saeed, Boyce, James and Sharifi, Salma (2022). Iterative seed word generation for interactive topic modelling: a mixed text processing and qualitative content analysis approach. International Conference on Information Systems (ICIS), Copenhagen, Denmark, 9-14 December 2022. Atlanta, GA United States: Association for Information Systems.
Namvar, Morteza, Boyce, James, Sarna, Jatin, Zheng, Yuanyuan, Chua Yeow Kuan, Alton and Ameli, Sina (2021). Moderating effects of time-related factors in predicting the helpfulness of online reviews: a deep learning approach. Hawaii International Conference on System Sciences 2021, Kauai, HI, United States, 5- 8 January 2021. Honolulu: IEEE Computer Society. doi: 10.24251/hicss.2021.092
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