Research On Influencing Factors And Effect Evaluation Of User Information Sharing Behavior In Network Community:an Information Ecology Perspective

With the rapid development of Internet technology,the impact of the Internet on people's lives and work is increasing day by day.The network community is a product growing rapidly and having great influence in the Internet era.At present,the network community has transitioned to the developing direction of branding construction and model growth,and has gradually moved toward the ecologicalization process.Users are the core strength of the development of the network community.Users can meet the information needs,expand their interaction circles,and improve their information literacy through sharing information in network community.Information ecology is a theory that studies the coordinated development of information subjects,information objects,information technology and information environment,which can provide a comprehensive interpretation framework for the study of various elements in a complex system environment.Therefore,this paper studies the information sharing problem in the network community based on the information ecological perspective.Based on a comprehensive review of domestic and foreign scholars' research on network community,information sharing and information ecology,the paper uses research methods like literature induction,knowledge map visualization,BP neural network,structural equation and case analysis,etc.to explore the mechanism,influencing factors,effect evaluation and sharing model of information sharing in network community.Mechanism research is the theoretical basis of the full text.Influential factors research is the focus of behavior analysis.Effect evaluation is the combination of theoretical indicator construction and actual community assessment.Sharing model research is the summary of information sharing of network community.Firstly,combined with the results of literature analysis,the paper constructs the network community information sharing mechanism model.The model consists of four main contents: the motivation of users' information sharing behavior,the network community information sharing ecosystem,and the network community information sharing ecological factor,and the niche of network community information sharing.Among them,the ecosystem is the theoretical basis of the full text,the ecological factor provides the dimension for the research on the influencing factors and effect evaluation of the network community information sharing,and the niche is the theoretical support for the analysis of the network community information sharing model.The network community information sharing mechanism model provides a theoretical framework and foundation for the study of the full text.Secondly,based on the theory of information ecological factor and the theory of technology acceptance,the model of network community information sharing influencing factors is constructed to study the impact on information sharing intent and information sharing behavior of different impact factors,from the perspective of the four dimensions of information people,information,information environment and information technology.Taking university students,the most important user groups of the online community as the research object,to obtain the questionnaire data,the reliability and validity of the data were tested by confirmatory factor analysis,and the proposed theoretical hypothesis was tested by the structural equation model.The analysis of the influencing factors of user information sharing in online community provides a new perspective for analyzing the information sharing behavior of online community users.Thirdly,based on the information ecological factor theory,the paper constructs the network community information sharing effect evaluation index system,and the BP neural network algorithm is used to test the index system.Then,the paper uses this index system to evaluate the effect of information sharing in the star network community(Logic Show,Xiaomi community,Xiaosong Pedia)and in the vertical network community(EEFF.net,Lijiang online,duorouunion home).The results show that the star community has a higher overall score due to its larger user scale,diversified information types,more information technology investment,and better sharing environment.In the future,the network community platforms need to increase investment in big data technology and community environmental governance to maintain user loyalty and build community brands.The analysis of the evaluation of the information sharing effect of the online community users can help to understand the actual situation of information sharing in the current popular online community and provide a realistic basis for future theoretical research.Finally,the information niche theory is used to analyze the model of network community information sharing,and two types of information sharing modes are proposed,namely interactive mode and integrated mode.The information sharing interaction mode includes an individual interaction mode and a public interaction mode,and the information sharing integration mode includes a platform integration mode and a user integration mode.Xiaomi community,the representative of star community and EEEE.net,the representative of vertical community are taken as a case study object to study the information sharing characteristics presented by the network communities under different modes.Further,the paper proposes the corresponding management strategies.The research of this paper,on the theoretical level,combined with the information ecology theory,provides a scientific method and analysis context for the research of network community information sharing.On the practical level,the questionnaire data is analyzed by Matlab software and AMOS software,which provides new methodological guidance for information sharing research in the network community.This research can help the network community create greater business value in the era of knowledge economy.In the future,based on the research of this paper,we will conduct in-depth research on the continuous information sharing behavior in network communities,various types of network community information behavior and community knowledge management.