Hongshu Chen

 

Dr Hongshu Chen is currently an Associate Professor with the School of Management, Beijing Institute of Technology, Beijing, China. She received the first Ph.D. degree in Management Science and Engineering from the Beijing Institute of Technology, in 2015, and the second Ph.D. degree in Software Engineering from the University of Technology Sydney, NSW, Australia, in 2016. Her research focuses on science & technology management and policy, scientific text mining, scientometrics and scholarly big data analytics, highlighting the application of AI-driven analytics for science, technology, and innovation studies. She has published more than 30 papers in refereed journals and conference proceedings in above fields, e.g., Research Policy (FT 50), Technological Forecasting and Social Change, IEEE Transactions on Engineering Management, IEEE Transactions on Cybernetics, Journal of Informetrics, Scientometrics and Knowledge-based Systems.

 

Research Interests

 

·               Science and Technology Management, Innovation Management

·               Scientometrics, Informetrics

·               AI4Science

·               Complex Networks, Scholarly Big Data

·               Scientific Text Mining and Analytics

·               Science and Technology Policies

 

Selected Publications

[1] Jin, Q., Chen, H.*, Wang, X. & Liu, J. 2026. Do synthesis programs facilitate interdisciplinary research? Evidence from the NSFC’s Major Research Plan. Research Policy, 55(2), 105379. (SSCI, FT 50, FMS A)

[2] Zhang, W., Wang, X.*, Chen, H., Liu, J. 2024. The impact of early debut on scientists: Evidence from the Young Scientists Fund of the NSFC. Research Policy, 53(2), 104935. (SSCI, FT 50, FMS A)

[3] Jin, Q., Chen, H.*, Wang, X., Xiong, F. 2024. How do network embeddedness and knowledge stock influence collaboration dynamics? Evidence from patents. Journal of Informetrics, 2024, 18(4): 101553. (SCI/SSCI, FMS B, JCR Q1)

[4] Jin, Q., Chen, H.*, Zhang, Y., Wang, X., Zhu, D. 2024. Unraveling Scientific Evolutionary Paths: An Embedding-Based Topic Analysis. IEEE Transactions on Engineering Management, 71: 8964-8978. (SCI/SSCI, FMS A, JCR Q1)

[5] CHEN, H., JIN, Q., WANG, X. & XIONG, F. 2022. Profiling academic-industrial collaborations in bibliometric-enhanced topic networks: A case study on digitalization research. Technological Forecasting and Social Change, 175, 121402. (SSCI, FMS B, JCR Q1)

[6] CHEN, H., SONG, X., JIN, Q. & WANG, X. 2022. Network Dynamics in University-industry Collaboration: A Collaboration-knowledge Dual-layer Network Perspective. Scientometrics, 127(11), 6637-6660. (SCI/SSCI, FMS B, JCR Q1)

[7] JIN, Q., CHEN, H.*, WANG, X., MA, T. & XIONG, F. 2022. Exploring funding patterns with word embedding-enhanced organization–topic networks: a case study on big data. Scientometrics, 127(9), 5415-5440. (SCI/SSCI, FMS B, JCR Q1)

[8] CHEN, H., WANG, X., PAN, S. & XIONG, F. 2021. Identify Topic Relations in Scientific Literature Using Topic Modeling. IEEE Transactions on Engineering Management, 68, 1232-1244. (SCI/SSCI, FMS A, JCR Q1)

[9] XIONG, F., SHEN, W., CHEN, H.*, PAN, S., WANG, X. & YAN, Z. 2020. Exploiting Implicit Influence from Information Propagation for Social Recommendation. IEEE Transactions on Cybernetics, 50, 4186-4199. (SCI, FMS B, JCR Q1)

[10] Chen, H., Zhang, G., Zhu, D., Lu, J. 2017. Topic-based technological forecasting based on patent data: A case study of Australian patents from 2000 to 2014. Technological Forecasting and Social Change, 119, 39-52. (SSCI, FMS B, JCR Q1)

 

Contact information

Add: 5 South Zhongguancun Street, Haidian District, Beijing 100081, P.R.China

Tel: 010-68918492

Email: hongshu.chen[at]bit.edu.cn