Research on the Relationship Network in Customer Innovation Community based on Text Mining and Social Network Analysis

Relationship is the focus of the current study in the social phenomenon with social network theory, which is mainly about its meaning and strength. However, a different object, different relationship. Social network theory insists that the actors behavior is the result of the limitations and opportunities of many relationships that occur simultaneously and interaction. The behavior and characteristics of the whole group are also dependent on the integration of multi-dimensional relationships. There are multidimensional relationships among customers participated product innovation in the customer innovation community. Since the huge number of customers in customer innovation community and the complex relationships among the customers, the method is different in traditional ways. Therefore, this paper combines associated crawler algorithm, text mining, and social network analysis to study network relationship types, network structure and the relevance of the customer innovation community. Firstly, this paper analyzes the relationship type and the relationship network according to previous studies. Secondly, reptile technology is used to obtain structured data in the customer community. After cleaning and pre-processing, the data is transformed into relational data from the original structure, with format 1069 x 1069 size matrix. Analyzing the structure of relationship network using social network analysis methods and tools, the results show that interactive network, social network, and knowledge-sharing networks are all sparse network. Thirdly, the correlation among the relationship networks is studied. The results demonstrate that it is higher than the correlation between the interactive network and the knowledge-sharing network and lower than the social network correlated with the other two networks.