Network-Structural Analysis of User Knowledge Collaboration Performance in Online Q&A Communities_Vol. 3 No. 4 (JMSD 2026)_Journal of Management and Social Development (ISSN: 3005-5741)

Home > Journal of Management and Social Development (ISSN: 3005-5741) > Vol. 3 No. 4 (JMSD 2026) >

Network-Structural Analysis of User Knowledge Collaboration Performance in Online Q&A Communities

Download PDF

DOI: https://doi.org/10.62517/jmsd.202612401

Author(s)

Huixuan Yang*

Affiliation(s)

Department of Information Management, Nanjing Agricultural University, Nanjing, Jiangsu, China *Corresponding Author

Abstract

Enhancing both the efficiency of collaboration and the quality of knowledge production continues to attract sustained attention in the management of information resources on online knowledge collaboration platforms. Drawing on a network-structural lens, this study investigates how user attributes, positions within the network, and interaction patterns manifested through comments collectively shape collaboration outcomes. A hypernetwork model underpins a multilayer framework linking users, content, and tags, with corresponding measures constructed at the individual, event, and network levels. Regression analysis combined with quadrant analysis is then employed to examine the proposed relationships. Results show that user activity exerts a significant influence on an individual's location within the network. At the event level, brokerage positions coincide with higher collaborative efficiency, while embeddedness in the network core bears a closer relation to collaboration quality. Interaction patterns distinguished by comment quality and participation intensity also diverge notably in their outcomes and structural properties, producing distinct forms of collaboration. By explaining how user attributes, network positions, and interaction patterns are interrelated and jointly shape collaboration performance, this study offers a structural basis for understanding and improving online knowledge collaboration.

Keywords

Knowledge Collaboration Performance; Hypernetwork; Social Network Structure; Interaction Patterns

References

[1] Faraj S, Jarvenpaa S L, Majchrzak A. Knowledge collaboration in online communities. Organization Science, 2011, 22(5): 1224-1239. [2] Zahedi M, Shahin M, Ali Babar M. A systematic review of knowledge sharing challenges and practices in global software development. International Journal of Information Management, 2016, 36(6): 995-1019. [3] Fritsch M, Kauffeld-Monz M. The impact of network structure on knowledge transfer: an application of social network analysis in the context of regional innovation networks. The Annals of Regional Science, 2008, 44(1): 21-38. [4] Boccaletti S, Bianconi G, Criado R, et al. The structure and dynamics of multilayer networks. Physics Reports, 2014, 544(1): 1-122. [5] Kivelä M, Arenas A, Barthelemy M, et al. Multilayer networks. Journal of Complex Networks, 2014, 2(3): 203-271. [6] De Domenico M, Granell C, Porter M A, et al. The physics of spreading processes in multilayer networks. Nature Physics, 2016, 12(10): 901-906. [7] Zhang H T, Ren L, Liu W L, et al. Research on user knowledge collaborative innovation based on hypernetwork: A case study of the open innovation community "Huafen Club" . Journal of Library and Information Science in Agriculture, 2021, 33(4): 74–81. [8] Tang H T, Li Z H, Qin R. Research on user knowledge model of mass collaborative innovation community based on hypernetwork. Chinese Journal of Management, 2017, 14(6): 859–867. [9] Feng C C, Yi M, Jin Y, et al. Research on the construction and application of a knowledge co-creation model for online health communities based on hypernetworks. Information Science, 1–20 [2026-04-05]. [10] Zhang X, Liu S, Chen X. Knowledge sharing in online communities: A meta-analysis. Information & Management, 2019, 56(3): 103136. [11] Zuo M, & Qiu J N. (2024). An exploratory analysis of the mechanisms of human–AI collaborative social knowledge construction in online knowledge communities in the context of generative AI. Information and Documentation Services, (4), 4–13. [12] Zhang Y, Zhu Q. Knowledge heterogeneity and team innovation: Evidence from online collaboration. Journal of Knowledge Management, 2022, 26(8): 1983-2001. [13] Li M, Sun Y, Lou H. The double-edged sword of knowledge diversity in online collaboration. Computers in Human Behavior, 2023, 139: 107500. [14] Chen X H, Hu P, & Zhou Y C. (2020). A study on the peer effects on knowledge contribution behavior of answerers in the Zhihu Q&A community. Documentation, Information & Knowledge, 37(4), 1034–1045. [15] Xu P, & Zhang D. (2018). An exploration of knowledge-sharing motivations in online Q&A communities: A social exchange theory perspective. Documentation, Information & Knowledge, 35(2), 105–112. [16] Lu Y Q, Yan X Y, & Ke J J. (2024). A study on the driving pathways of user knowledge contribution behavior on open innovation platforms. Library and Information Service, 68(21), 120–132. [17] Kang L L, Song Y J, & Chen J. (2022). The influence of gamification design on user retention in knowledge communities: A case study of the badge mechanism. Documentation, Information & Knowledge, 39(6), 45–54. [18] Shi Z, Rui H, Whinston A B. Content sharing in a social broadcasting environment. MIS Quarterly, 2020, 44(1): 1-27. [19] Ma M, Agarwal R. Through a glass darkly: Information technology design, identity verification, and knowledge contribution in online communities. Information Systems Research, 2021, 32(2): 456-473. [20] Yang R X, Yu Z J, Zhong Q, Liu L L, & Wei H N. (2024). Research on the identification of core users in online knowledge communities integrating multiple user attributes: A LeaderRank algorithm based on sentiment weighting. Journal of the China Society for Scientific and Technical Information, 43(6), 118–132. [21] Kumar S, Hamilton W L, Leskovec J, et al. Community interaction and conflict on the web. Proceedings of the Web Conference, 2018: 933-943. [22] Chen T, Zhang R, Xu K. Identifying influential users in online knowledge communities: A network-based approach. Expert Systems with Applications, 202 4,235: 121234. [23] Anderson A, Huttenlocher D, Kleinberg J, et al. Effects of user interaction on content quality in online Q&A communities. Proceedings of ICWSM, 2020. [24] Zhou Y, Li X, Zhao K. Role differentiation and knowledge contribution in online Q&A communities. Information Processing & Management, 2023, 60(2): 103210. [25] Liu Y Y, Jiang S. Research on social network analysis and knowledge sharing management based on big data . Information Science, 2019, 37(4): 109–115. [26] Feng D M, Wu C J, Zhang R X. Research on the reciprocal knowledge-sharing relationships within the organization of large complex engineering projects based on SNA . Science and Technology Management Research, 2019, 39(20): 169–175. [27] Wei L, Zhang W L. Research on the knowledge-sharing network model of OA software enterprises based on SNA. Science-Technology and Management, 2019, 21(1): 55–61. [28] Cao H J, Chen Y Q. How do differences in policy deconstruction shape the structure of inter-departmental collaboration networks?—A social network analysis of inter-departmental collaboration at the municipal and county levels. Administrative Tribune, 2021, 28(4): 73–82. [29] Gu J H, Jiang Y F, Zhang L, et al. A co-evolution model of opinions and behaviors based on multilayer networks. Complex Systems and Complexity Science, 1–9 [2026-04-10]. [30] Li Y T, Ma F C. Research on social network analysis based on tag co-occurrence. Journal of Intelligence, 2012, 31(7): 103–109. [31] Broido A D, Clauset A. Scale-free networks are rare. Nature Communi-cations, 2019, 10(1): 1017. [32] Zhang J, Ackerman M S, Adamic L. Expertise networks in online communities: Structure and algorithms. Proceedings of WWW, 2020. [33] Pei L. The application and development of social network analysis in information science. Information and Documentation Services, 2006, (6): 40–46. [34] Yang J, McAuley J, Leskovec J. Community detection in networks: A user guide and review. ACM Computing Surveys, 2021, 54(3): 1-37. [35] Singh P V, Tan Y, Mookerjee V. Network effects and the diffusion of innovations in online communities. Information Systems Research, 2022, 33(1): 1-20. [36] Ni Z N, Wang C Y, Si X Y. A social network perspective on the differences between knowledge sharing and misinformation dissemination in online health communities. Information Studies: Theory & Application, 2023, 46(7): 67–75. [37] Liu Y Y, Jiang S. Research on social network analysis and knowledge sharing management based on big data. Information Science, 2019, 37(4): 109–115. [38] Liu R J, Zhong X J, Meng T N, et al. Research on the structural characteristics of scientific research collaboration networks in large scientific facilities. Journal of Xi'an Jiaotong University (Social Sciences), 2023, 43(6): 140–151. [39] Burt R S. Structural holes and good ideas. American Journal of Sociology, 2017, 110(2): 349-399. [40] Contractor N S, Monge P R, Leonardi P M. Multidimensional networks and the dynamics of sociomateriality: Bringing technology inside the network. International Journal of Communication, 2020, 14: 1-23.