Title: A knowledge sharing method for virtual academic community based on social network analysis

Authors: Xiaolin Zhang; Miao Wang

Addresses: Teacher and Teaching Developing Centre of Dalian Ocean University, Dalian, China ' College of International Education, Liaoning Normal University, Dalian, Liaoning, China

Abstract: Studying knowledge sharing in virtual academic community is meaningful for a deep understanding of knowledge dissemination and sharing mechanisms, as well as for enhancing the knowledge level within these communities. To overcome the low success rate, long response time and low satisfaction of traditional methods, a knowledge sharing method for virtual academic community based on social network analysis is proposed. The method analyses the social network of knowledge exchange among users in virtual academic community, achieves knowledge discovery within these communities and aggregation processing the knowledge. The knowledge sharing model is built using the state space modelling approach to realise knowledge sharing within the community. Experimental results demonstrate that the proposed method achieves a maximum success rate of 98.2% for knowledge sharing, a maximum response time of 0.51 s and an average satisfaction level of 96.6.

Keywords: social network analysis; virtual academic community; knowledge sharing; aggregation processing; state space modelling; knowledge sharing model.

DOI: 10.1504/IJCAT.2023.138841

International Journal of Computer Applications in Technology, 2023 Vol.73 No.4, pp.313 - 322

Received: 10 Jul 2023
Accepted: 15 Dec 2023
Published online: 31 May 2024 *

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