Online knowledge sharing in blockchains: towards increasing participation

Abstract

PurposeThis paper aims to propose a system dynamics model of blockchain online community knowledge sharing, with the following goals: to reveal the internal mechanism of blockchain technology on community knowledge sharing; to show the impact of blockchain technology on knowledge sharing; and to promote knowledge sharing and the self-development of blockchain online communities.Design/methodology/approachBased on the core characteristic factors of blockchain technology, including incentive mechanism, trust mechanism, information protection mechanism, etc., a knowledge sharing analysis framework is established. Through the use of the Vensim PLE (Personal Learning Version) software, according to the steps of “putting forward a dynamic hypothesis”, “establishing a system dynamic equations”, and then “model testing” and “simulation”, the article analyzes in depth the process and extent of the impact of the above features on online community knowledge sharing.FindingsThe results show that the blockchain incentive mechanism, trust mechanism and information protection mechanism all contribute to promoting an increase in the number of community knowledge sharing users, as well as in the total amount of knowledge shared. The results also show that the token reward in the incentive mechanism has in fact a higher degree of influence than the trust and information protection mechanisms.Originality/valueAt present, no research on the internal mechanism of knowledge sharing in blockchain online communities has been carried out. This article plays a complementary role in research in this field, and offers significant guidance for promoting online community knowledge management and online community development.

Recognition of opinion leaders in blockchain-based social networks by structural information and content contribution

“…Meanwhile, the blockchain social networking platforms have added interactive features such as user reputation, voting, and bounties to change user characteristics and interaction behaviors ( Duan et al, 2020 ). Under the influence of consensus mechanism ( Zheng & Boh, 2021 ), irreversibility ( Yan et al, 2021 ), and mechanism of valuable content ( Bai et al, 2021 ), users who create and discover quality content and actively contribute to the community are more influential than those who have better network position ( Xie & Zhang, 2023 ). Therefore, analyzing user characteristics and behaviors ( Girgin, 2021 ) can better identify opinion leaders in blockchain social networks.…”