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School of Business and Management

Xiancheng Li

 Xiancheng Li

Email: x.l.li@qmul.ac.uk

Biography

Xiancheng Li is a post-doctoral researcher, currently working with Professor Pietro Panzarasa and Dr. Anna de Simoni. He works in the AD HOC program (https://www.qmul.ac.uk/adhoc/), which aims to help people with troublesome asthma to better control their symptoms and improve their quality of life, by engaging with other people with asthma in an online community.

Before joining AD HOC team, Xiancheng Li was completing his PhD in the Centre for Globalisation Research at the School of Business and Management, Queen Mary University of London. His doctoral research focused on academic collaborations and innovation, applying a combination of network science, machine learning, and econometric methods. In particular, he investigated how key decisions made by scientists throughout their careers can influence their long-term success.

Teaching 

  • Teaching Associate, Machine Learning and Digital Technology, 2023-2024 and 2024-2025
  • Teaching Associate, Social Network Analysis, 2020

Research Interests

Xiancheng’s research interests currently centre around discovering the network patterns of users’ engagement in online health communities and evaluating the correlation between network properties and users’ health-related outcomes. He is also interested in applying natural language processing to provide an in-depth understanding of the evolution of essential themes, keywords and topics discussed in communities.

Selected Publications

  1. Li X, Vaghi E, Pasi G, Coulson NS, De Simoni A, Viviani M; AD HOC Group. Understanding the Engagement and Interaction of Superusers and Regular Users in UK Respiratory Online Health Communities: Deep Learning-Based Sentiment Analysis. J Med Internet Res. 2025 Feb 13;27:e56038.
  2. Sun Y, Caccioli F, Li X, Livan G. The academic Great Gatsby Curve. Journal of the Royal Society Interface. 2024 Aug 14;21(217):20240173.
  3. Li X, Gill A, Panzarasa P, Bestwick J, Schrag A, Noyce A, De Simoni A. Web Application to Enable Online Social Interactions in a Parkinson Disease Risk Cohort: Feasibility Study and Social Network Analysis. JMIR Formative Research. 2024 May 24.
  4. Karampatakis GD, Kimber S, Wood HE, Griffiths CJ, Taylor SJ, Li X, Day B, Mant J, Relton C, Watson JS, Marsh V. Development of the face-to-face component and recruitment strategy of a primary care digital social intervention for patients with asthma: Qualitative focus groups and interviews with stakeholders. European Journal of General Practice. 2024 Dec 31;30(1):2407594.
  5. Karampatakis GD, Wood HE, Griffiths CJ, Taylor SJ, Toffolutti V, Bird VJ, Lea NC, Ashcroft RE, Day B, Coulson NS, Panzarasa P, Li X. Non-randomised feasibility study testing a primary care intervention to promote engagement in an online health community for adults with troublesome asthma: protocol. BMJ open. 2023 Jul 1;13(7):e073503.
  6. Li X, Verginer L, Riccaboni M, Panzarasa P. A network approach to expertise retrieval based on path similarity and credit allocation. Journal of Economic Interaction and Coordination. 2022 Apr;17(2):501-33.
  7. Li X, Rong W, Shi H, Tang J, Xiong Z. The impact of conference ranking systems in computer science: A comparative regression analysis. Scientometrics. 2018 Aug;116:879-907.

Scholarly Contributions

  1. Poster presentation at the Primary Care Respiratory Society (PCRS) Respiratory Conference, 2024, Telford, UK
  2. Oral presentation at 8th International Conference on Computational Social Science, 2022, Chicago, IL USA (Online)
  3. Oral presentation at SBM PhD Symposium, 2021, QMUL, UK (Online).
  4. Oral presentation at 7th International Conference on Computational Social Science, 2021, Zurich Switzerland (Online).
  5. Oral presentation at SBM PhD Symposium, 2020, QMUL, UK (Online).
  6. Oral and poster presentation at 6th International Conference on Computational Social Science, 2020, MA USA (Online).
  7. Oral presentation at SBM PhD Symposium, 2019, QMUL, UK
  8. Poster presentation at 5th International Conference on Computational Social Science, 2019, Amsterdam, Netherlands.
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