Have a personal or library account? Click to login
Understanding teams and productivity in information retrieval research: Academia, industry, and cross-community collaborations Cover

Understanding teams and productivity in information retrieval research: Academia, industry, and cross-community collaborations

By: Jiaqi Lei,  Liang Hu,  Yi Bu and  Jiqun Liu  
Open Access
|Oct 2025

References

  1. Ahmed, N., Wahed, M., & Thompson, N. C. (2023). The growing influence of industry in AI research. Science, 379(6635), 884–886. https://doi.org/10.1126/science.ade2420
  2. Castillo, C. (2019). Fairness and Transparency in Ranking. ACM SIGIR Forum, 52(2), 64–71. https://doi. org/10.1145/3308774.3308783
  3. Culpepper, J. S., Diaz, F., & Smucker, M. D. (2018). Research Frontiers in Information Retrieval: Report from the Third Strategic Workshop on Information Retrieval in Lorne (SWIRL 2018). ACM SIGIR Forum, 52(1), 34–90. https://doi.org/10.1145/3274784.3274788
  4. Ekstrand, M. D., Burke, R., & Diaz, F. (2019). Fairness and Discrimination in Retrieval and Recommendation. Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, 1403–1404. https://doi.org/10.1145/3331184.3331380
  5. Etzkowitz, H., & Leydesdorff, L. (2000). The dynamics of innovation: From National Systems and “Mode 2” to a Triple Helix of university–industry–government relations. Research Policy, 29(2), 109–123. https://doi. org/10.1016/S0048-7333(99)00055-4
  6. Gao, J., Xiong, C., & Bennett, P. (2020). Recent Advances in Conversational Information Retrieval. Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, 2421–2424. https://doi.org/10.1145/3397271.3401418
  7. Gao, R., & Shah, C. (2021). Addressing Bias and Fairness in Search Systems. Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2643–2646. https://doi. org/10.1145/3404835.3462807
  8. Garfield, E. (1996). Fortnightly Review: How can impact factors be improved? BMJ, 313(7054), 411–413. https://doi.org/10.1136/bmj.313.7054.411
  9. Hu, B., Ding, Y., Dong, X., Bu, Y., & Ding, Y. (2021). On the relationship between download and citation counts: An introduction of Granger-causality inference. Journal of Informetrics, 15(2), 101125. https://doi.org/10.1016/j.joi.2020.101125
  10. Jasny, B. R., Wigginton, N., McNutt, M., Bubela, T., Buck, S., Cook-Deegan, R., Gardner, T., Hanson, B., Hustad, C., Kiermer, V., Lazer, D., Lupia, A., Manrai, A., McConnell, L., Noonan, K., Phimister, E., Simon, B., Strandburg, K., Summers, Z., & Watts, D. (2017). Fostering reproducibility in industry-academia research. Science, 357(6353), 759–761. https://doi.org/10.1126/science.aan4906
  11. Jazi, S. Y., Mirzaeinia, A., & Jazi, S. Y. (2024). Analyzing Gender Polarity in Short Social Media Texts with BERT: The Role of Emojis and Emoticons.https://doi.org/10.13140/RG.2.2.15772.50568
  12. Keyvan, K., & Huang, J. X. (2023). How to Approach Ambiguous Queries in Conversational Search: A Survey of Techniques, Approaches, Tools, and Challenges. ACM Computing Surveys, 55(6), 1–40. https://doi.org/10.1145/3534965
  13. Kobayashi, M., & Takeda, K. (2000). Information retrieval on the web. ACM Computing Surveys, 32(2), 144–173. https://doi.org/10.1145/358923.358934
  14. Lei, J., Bu, Y., & Liu, J. (2023). Information Retrieval Research in Academia and Industry: A Preliminary Analysis of Productivity, Authorship, Impact, and Topic Distribution. In I. Sserwanga, A. Goulding, H. Moulaison-Sandy, J. T. Du, A. L. Soares, V. Hessami, & R. D. Frank (Eds.), Information for a Better World: Normality, Virtuality, Physicality, Inclusivity (Vol. 13972, pp. 360–370). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-28032-0_29
  15. Li, H., & Lu, Z. (2016). Deep Learning for Information Retrieval. Proceedings of the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval, 1203–1206. https://doi.org/10.1145/2911451.2914800
  16. Liu, J. (2021). Deconstructing search tasks in interactive information retrieval: A systematic review of task dimensions and predictors. Information Processing & Management, 58(3), 102522. 10.1016/j. ipm.2021.102522
  17. Marijan, D., & Gotlieb, A. (2021). Industry-Academia research collaboration in software engineering: The Certus model. Information and Software Technology, 132, 106473. https://doi.org/10.1016/j.infsof.2020.106473
  18. Mitchell, M., Wu, S., Zaldivar, A., Barnes, P., Vasserman, L., Hutchinson, B., Spitzer, E., Raji, I. & Gebru, T. (2019, January). Model cards for model reporting. In Proceedings of the Conference on Fairness, Accountability, and Transparency (pp. 220-229). 10.1145/3287560.3287596
  19. Noyons, E. C. M., Van Raan, A. F. J., Grupp, H., & Schmoch, U. (1994). Exploring the science and technology interface: Inventor-author relations in laser medicine research. Research Policy, 23(4), 443–457. https://doi.org/10.1016/0048-7333(94)90007-8
  20. Olteanu, A., Garcia-Gathright, J., De Rijke, M., Ekstrand, M. D., Roegiest, A., Lipani, A., Beutel, A., Olteanu, A., Lucic, A., Stoica, A.-A., Das, A., Biega, A., Voorn, B., Hauff, C., Spina, D., Lewis, D., Oard, D. W., Yilmaz, E., Hasibi, F., … Kamishima, T. (2019). FACTS-IR: Fairness, accountability, confidentiality, transparency, and safety in information retrieval. ACMSIGIR Forum, 53(2), 20–43. https://doi.org/10.1145/3458553.3458556
  21. Owen-Smith, J. (2003). From separate systems to a hybrid order: Accumulative advantage across public and private science at Research One universities. Research Policy, 32(6), 1081–1104. https://doi.org/10.1016/S0048-7333(02)00111-7
  22. Perkmann, M., & Walsh, K. (2009). The two faces of collaboration: Impacts of university-industry relations on public research. Industrial and Corporate Change, 18(6), 1033–1065. https://doi.org/10.1093/icc/dtp015
  23. Rani, Y. A., Balaram, A., Sirisha, M. R., Nabi, S. A., Renuka, P., & Kiran, A. (2024). AI Enhanced Customer Service Chatbot. 2024 International Conference on Science Technology Engineering and Management (ICSTEM), 1–5. https://doi.org/10.1109/ICSTEM61137.2024.10561155
  24. Rhoten, D., & Powell, W. W. (2007). The Frontiers of Intellectual Property: Expanded Protection versus New Models of Open Science. Annual Review of Law and Social Science, 5(1), 345–373. https://doi.org/10.1146/annurev.lawsocsci.3.081806.112900
  25. Sanh, V., Debut, L., Chaumond, J., & Wolf, T. (2020). DistilBERT, a distilled version of BERT: Smaller, faster, cheaper and lighter (No. arXiv:1910.01108). arXiv. http://arxiv.org/abs/1910.01108
  26. Schloegl, C., & Gorraiz, J. (2011). Global usage versus global citation metrics: The case of pharmacology journals. Journal of the American Society for Information Science and Technology, 62(1), 161–170. https://doi.org/10.1002/asi.21420
  27. Serajian, M., Marini, S., Alanko, J. N., Noyes, N. R., Prosperi, M., & Boucher, C. (2023). Scalable De Novo Classification of Antibiotic Resistance of Mycobacterium Tuberculosis. Bioinformatics. https://doi.org/10.1101/2023.11.16.567394
  28. Shahin, M., Chen, F. F., Hosseinzadeh, A., Maghanaki, M., & Eghbalian, A. (2024). A novel approach to voice of customer extraction using GPT-3.5 Turbo: Linking advanced NLP and Lean Six Sigma 4.0. The International Journal of Advanced Manufacturing Technology, 131(7–8), 3615–3630. https://doi.org/10.1007/s00170-024-13167-w
  29. Spicer, A. J., Colcomb, P.-A., & Kraft, A. (2022). Mind the gap: Closing the growing chasm between academia and industry. Nature Biotechnology, 40(11), 1693–1696. https://doi.org/10.1038/s41587-022-01543-4
  30. Thomas, P., Czerwinksi, M., Mcduff, D., & Craswell, N. (2021). Theories of Conversation for Conversational IR. ACM Transactions on Information Systems, 39(4), 1–23. https://doi.org/10.1145/3439869
  31. Van Looy, B., Callaert, J., & Debackere, K. (2006). Publication and patent behavior of academic researchers: Conflicting, reinforcing or merely co-existing? Research Policy, 35(4), 596–608. https://doi.org/10.1016/j. respol.2006.02.003
  32. Wuchty, S., Jones, B. F., & Uzzi, B. (2007). The Increasing Dominance of Teams in Production of Knowledge. Science, 316(5827), 1036–1039. https://doi.org/10.1126/science.1136099
  33. Yates, A., Nogueira, R., & Lin, J. (2021). Pretrained Transformers for Text Ranking: BERT and Beyond. Proceedings of the 14th ACM International Conference on Web Search and Data Mining, 1154–1156. https://doi.org/10.1145/3437963.3441667
  34. Zaharia, N., & Kaburakis, A. (2016). Bridging the Gap: U.S. Sport Managers on Barriers to Industry–Academia Research Collaboration. Journal of Sport Management, 30(3), 248–264. https://doi.org/10.1123/jsm.2015-0010
  35. Zamani, H., Dumais, S., Craswell, N., Bennett, P., & Lueck, G. (2020). Generating Clarifying Questions for Information Retrieval. Proceedings of The Web Conference 2020, 418–428. https://doi.org/10.1145/3366423.3380126
  36. Zhang, C., Bu, Y., Ding, Y., & Xu, J. (2018). Understanding scientific collaboration: Homophily, transitivity, and preferential attachment. Journal of the Association for Information Science and Technology, 69(1), 72–86. https://doi.org/10.1002/asi.23916
DOI: https://doi.org/10.2478/jdis-2025-0051 | Journal eISSN: 2543-683X | Journal ISSN: 2096-157X
Language: English
Submitted on: Jun 6, 2025
Accepted on: Sep 19, 2025
Published on: Oct 16, 2025
Published by: Chinese Academy of Sciences, National Science Library
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2025 Jiaqi Lei, Liang Hu, Yi Bu, Jiqun Liu, published by Chinese Academy of Sciences, National Science Library
This work is licensed under the Creative Commons Attribution 4.0 License.

AHEAD OF PRINT