Analyzing & Clustering Enterprise Microblog Users with Supernetwork
Xi Yunjiang1,Du Diedie1,Liao Xiao2(),Zhang Xuehong1
1School of Business Administration, South China University of Technology, Guangzhou 510641, China 2School of Internet Finance and Information Engineering, Guangdong University of Finance,Guangzhou 510521, China
[Objective] This paper proposes an integrated modeling method to process multi-dimensional user interest data, aiming to examine the spectral clustering method for analyzing user interests. [Methods] First, we retrieved Weibo (Microblog) data of "Three Squirrels" and used supernetwork model to integrate the modeling of contents and user interaction data. Then, we constructed an interactive interest index and grouped the users with spectral clustering algorithm. Finally, we evaluated the clustering results with the Silhouette Coefficient and Davies-Bouldin methods. [Results] We found that the clustering DB value reached 0.57 (k was set at 15), which was evenly distributed. [Limitations] More research is needed to further explore user characteristic data and the impacts of different data dimensions on user interests. [Conclusions] This study proposes maintenance and marketing suggestions for enterprise Weibo profiles, which will help them identify user interests and improve marketing effectiveness.
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