A new model to measure the knowledge diffusion via information entropy in virtual communities

Xiangyu Wang, Junwang, Ou Liu
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Abstract

In order to measure the different values of a great number of knowledge spreading in virtual communities, we build a knowledge diffusion measurement model based on information entropy. The model quantifies the knowledge entropy of different nodes in the spreading process in terms of users' behaviors. Consequently, transmitted knowledge can be sorted by the knowledge entropy, making the measurement of knowledge values and knowledge diffusion more accurately.
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基于信息熵测度虚拟社区知识扩散的新模型
为了衡量虚拟社区中大量知识传播的不同价值,建立了基于信息熵的知识传播度量模型。该模型根据用户行为量化传播过程中不同节点的知识熵。利用知识熵对传播的知识进行排序,使知识价值和知识扩散的度量更加准确。
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