股吧关注网络与股票市场的关联性分析  

Associations Between Following Network of Online Investment Community and Stock Market

作　　者：李雨露 赵吉昌[1] Li Yulu;Zhao Jichang(School of Economics and Management,Beihang University,Beijing 100191,China)

机构地区：[1]北京航空航天大学经济管理学院,北京100191

出　　处：《数据分析与知识发现》2023年第6期134-147,共14页Data Analysis and Knowledge Discovery

基　　金：国家自然科学基金项目(项目编号:71871006)的研究成果之一。

摘　　要：【目的】探究股吧用户关注网络中用户的股票偏好及其社交结构与股票市场的关联性。【方法】采用统计分析的方法对股吧用户偏好进行观察,采用复杂网络分析方法对用户关注网络的结构特征进行度量,采用关联性分析的方法建立模型,研究网络结构与股票价格波动的相关性并进行显著性检验。【结果】股吧用户关注网络中存在关注关系的用户在股票偏好上更相似(K-S test~0.235,p~0),网络的结构会影响信息的传播结果,进而与股票价格的相似波动关联,其中网络效率这一结构变量的系数显著为负(p~0.01)。相关结果暗示关注网络传播信息的能力越强,股票价格的波动将越独立于其他股票和市场平均水平的波动,增加关注网络传播信息的能力可减少股价共同振荡。【局限】缺乏对不同社交平台数据的实验验证和分析比较。【结论】本文研究方法和结果可以为市场监管和投资者的投资行为提供一定的启示。[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.

关 键 词：社交媒体 用户关注网络 股票价格波动 关联性分析 信息传播能力 

分 类 号：TP391[自动化与计算机技术—计算机应用技术] G35[自动化与计算机技术—计算机科学与技术]