| Predicting Adoption Probabilities in Social Networks X Fang, P Hu, ZL Li, W Tsai Information Systems Research 24 (1), 128-145, 2013 | 192 | 2013 |
| Analysis of the query logs of a web site search engine M Chau, X Fang, OR Liu Sheng Journal of the American Society for Information Science and Technology 56 …, 2005 | 149 | 2005 |
| Online consumer search depth: Theories and new findings J " Jennifer" Zhang, X Fang, OR Liu Sheng Journal of Management Information Systems 23 (3), 71-95, 2006 | 118 | 2006 |
| A survey of link recommendation for social networks: Methods, theoretical foundations, and future research directions Z Li, X Fang, ORL Sheng ACM Transactions on Management Information Systems (TMIS) 9 (1), 1-26, 2017 | 83 | 2017 |
| Examining the mediating roles of cognitive load and performance outcomes in user satisfaction with a website PJH Hu, H Hu, X Fang Mis Quarterly 41 (3), 975-A11, 2017 | 81 | 2017 |
| Utility-based Link Recommendation for Online Social Networks Z Li, X Fang, X Bai, O Sheng Management Science (forthcoming), 2015 | 77 | 2015 |
| Web searching in Chinese: A study of a search engine in Hong Kong M Chau, X Fang, CC Yang Journal of the American Society for Information Science and Technology 58 (7 …, 2007 | 69 | 2007 |
| Mobile app recommendation: An involvement-enhanced approach J He, X Fang, H Liu, X Li Available at SSRN 3279195, 2018 | 65 | 2018 |
| Top persuader prediction for social networks X Fang, PJH Hu MIS Quarterly 42 (1), 63-A14, 2018 | 58 | 2018 |
| Machine Learning in Information Systems Research. B Padmanabhan, X Fang, N Sahoo, A Burton-Jones MIS Quarterly 46 (1), 2022 | 54 | 2022 |
| A data-driven approach to measure web site navigability X Fang, PJH Hu, M Chau, HF Hu, Z Yang, ORL Sheng Journal of Management Information Systems 29 (2), 173-212, 2012 | 54 | 2012 |
| LinkSelector: A Web mining approach to hyperlink selection for Web portals X Fang, ORL Sheng ACM Transactions on Internet Technology (TOIT) 4 (2), 209-237, 2004 | 47 | 2004 |
| Inference-based Naïve Bayes:Turning Naïve Bayes Cost-sensitive X Fang IEEE Transactions on Knowledge and Data Engineering 25 (10), 2302-2313, 2013 | 41 | 2013 |
| When is the right time to refresh knowledge discovered from data? X Fang, ORL Sheng, P Goes Operations Research 61 (1), 32-44, 2013 | 38 | 2013 |
| Understanding Medication Nonadherence from Social Media: A Sentiment-Enriched Deep Learning Approach. J Xie, X Liu, D Dajun Zeng, X Fang MIS Quarterly 46 (1), 2022 | 26 | 2022 |
| Bias of AI-generated content: an examination of news produced by large language models X Fang, S Che, M Mao, H Zhang, M Zhao, X Zhao Scientific Reports 14 (1), 5224, 2024 | 25 | 2024 |
| A deep learning–based, unsupervised method to impute missing values in electronic health records for improved patient management D Xu, PJH Hu, TS Huang, X Fang, CC Hsu Journal of Biomedical Informatics 111, 103576, 2020 | 25 | 2020 |
| A prescriptive analytics method for cost reduction in clinical decision making X Fang, Y Gao, PJ Hu MIS Quarterly, Forthcoming, 2019 | 22 | 2019 |
| Characteristics of character usage in Chinese Web searching M Chau, Y Lu, X Fang, CC Yang Information processing & management 45 (1), 115-130, 2009 | 20 | 2009 |
| Designing a better web portal for digital government: a web-mining based approach X Fang, ORL Sheng DG. O 2005, 277-278, 2005 | 19 | 2005 |
