[Objective] This paper explores the stock preference in the following network of Guba (a Chinese online investment community) users. It examines the correlation between the stock market performance and the social structures of the network. [Methods] First, we used statistical analysis to study users’ preferences. Then, we utilized complex network analysis to learn the structural characteristics of the users’ following network. Finally, we conducted a correlation analysis to examine the correlations between network structures and stock price fluctuations. [Results] Users with the following relationships in the network are more similar in their stock preference (K-S test~0.235, p~0). The structures of the following network affect the dissemination of information, which is significantly correlated to the fluctuation of stock prices. The structural variables of network efficiency are significantly negative (p~0.01). Our findings suggest that the stronger the ability of the following network to spread information, the more independent the fluctuation of stock price will be from the fluctuation of other stocks and the market average. Increasing the ability to disseminate information on the following network can reduce the co-oscillation of the stock price in China. [Limitations] This study lacks experimental validation and analysis comparison of data from different social platforms. [Conclusions] The research methods and results presented in this paper can provide some guidance for market regulation and stock investment.
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