Research On The Influence Of Knowledge Social Mechanism On Knowledge Collaboration Of Internet Communities

In the era of knowledge economy,due to the rapid development and popularization of Internet technology,the knowledge production model has undergone significant changes.According to the data of China Internet Network Information Center(CNNIC)as of June 2019,China's Internet users reached 854 million,of which China's social network users reached 825 million,accounting for 96.5% of China's overall Internet users.Internet social products have become It is an indispensable tool for people to acquire knowledge and innovate knowledge.Under the background of this era,starting from the mechanism of knowledge socialization,exploring its impact on the structure of community relations,and then on the impact of community knowledge collaboration,has become a theoretical issue of great practical significance.Under the above realistic background,this paper abstracts the knowledge social platform,takes the most essential knowledge network community based on knowledge social relations as the research object,adopts computational experimental research methods,and attempts to learn from the knowledge social mechanism-community relationship structure-community knowledge A three-stage paradigm of collaboration to study the impact of knowledge and social mechanisms on social network knowledge collaboration.Specifically,first of all,based on the social relationship network is the premise of community knowledge collaboration,this paper proposes a random knowledge social mechanism,popular knowledge social mechanism and complementary knowledge social mechanism,and accordingly constructs a random social network model,popular social network model and complementary social network model.Analysis of the relationship distribution structure of the social network,the results show that the relationship structure between the popular social network and the complementary social network has a distribution characteristic of dark law,and the distribution characteristic of the popular social network is stronger;The relationship structure is evenly distributed.Secondly,in view of the diversity and complexity of learning,innovation,and ability evolution in the process of community knowledge collaboration,this article builds a community knowledge collaboration model that includes knowledge learning,knowledge innovation and learning ability,and innovation ability evolution,based on existing research.The analysis results of computational experiments based on this model show that there is a co-evolution phenomenon of community knowledge stock,community learning ability and community innovation ability.In different social networks,there is a clear difference among the evolution of community knowledge stock,community learning ability and community innovation ability.Among them,the random community network is most conducive to the improvement of community knowledge stock and community learning ability,and the popular community network is most conducive to the improvement of community innovation ability.Finally,due to the random nature of the computational experimental method,this paper conducts a sensitivity analysis of the main research conclusions of this paper from the aspects of the number of social relationships and the number of individuals in the community,and the results verify the robustness of the results of this study.Compared with existing related research,there are three main innovations in this article.First,this article innovatively proposes a random knowledge social mechanism,a popular knowledge social mechanism,and a complementary knowledge social mechanism,and further deeply integrates the dynamic connection between the knowledge social mechanism and the social network relationship structure.Second,given the total amount of resources owned by an individual,the allocation of individual resources for knowledge learning and knowledge innovation has an important impact on the evolution of their learning and innovation capabilities.Based on this consideration,this article assumes that individuals aim to maximize relative knowledge stocks,and then considers the substitution effect between individual knowledge learning and individual knowledge innovation.Based on this substitution effect,the mathematical model characterization and computational experimental research methods make this article to deeply study the common dynamic evolution of community knowledge stock,community learning ability and community innovation ability.Third,due to the dynamic evolution of community knowledge collaboration problems and the dynamic adaptation of micro-individuals,this paper uses computational experimental methods to organically link the micro-foundation of individual behavior and the phenomenon of community knowledge collaboration,which in turn allows this article to be deeper.Study the process mechanism of the difference of knowledge collaboration results of network communities with different structures.