Research On The Impact Of Microblog Comments On The Decision-making Behavior Of Individual Investors In The Stock Marke

The revolutionary development of Internet has been continuously changing the way people retrieve information and make decisions,particularly because of the wide Internet coverage and progressive education level,Internet is the primary channel for investors to acquire information.Microblogging has drawn much attention as an emerging medium for spreading popular information.Individual investors as a vulnerable group on the stock market display a low level of rationality in investment decision-making,partly because of personal cognitive bias and partly because of external interference.The speeding development of social media supplies an important source of information which lands a great impact on the decision-making of individual investors.To stimulate individual investor trading via microblogging which leads to market fluctuation is not unseen,while few studies are conducted on how microblogging reviews interfere with the decision-making of individual investors.Based on testing the existence of influential effects,this study will explore the influential factors and mechanism,identify key factors and effect path,and propose the theories and applications of how microblogging reviews affect the decisions-making of individual investors.The study adopts both qualitative and quantitative research methodology.It screens related theories and microblogging applications,then proposing a conceptual model for the mechanism of how microblogging reviews affect individual investors.In modeling the influencing mechanism,the study employs causal Bayesian network,collecting genuine historic data for the modeling to learn topological structure and parameters.The purpose is to explore the mechanism of how microblogging reviews affect individual investors,and to identify the key influential factors and operational path.First,the study conducts an analysis on the influencial effect of microblogging reviews on stock market individual investors,providing empirical evidence for its existence.Second,it screens the up to date research findings and the Sina Stock Microblogging’s applications,integrating microblog features and online reviews’impacts on investors,to seek influential factors of microblog reviews on investment decision-making,build a domain-specific lexicon,and establish the quantization scheme of relevant constructs in the context of big data.Third,the application of Bayesian network with the combination of knowledge and data training models on the influencing mechanism,which is grounded on the theories of the decision making behaviors of individual investors,such as TRA,and the theories and practices of microblog reviews,and construct the topology of prior Bayesian network.Subsequently,a crawler is compiled to extract relevant information from the Sina Microblogging and to quantize the constructs so as to produce target data sets.The results are connected to the real-time stock market exchange data as output,which feeds the Bayesian network learning.The posterior Bayesian network after topological and parameter learning reflects the influencial mechanism of how microblogging reviews affect individual investors.This network pins down investor attention,sentiment,objectivity and popularity of microblogging as key factors.All those factors affect the investment behaviors via working on the individual investors’attitude of information adoption.Finally,the findings in theory provide suggestions to the surveillance of publicly listed companies.This study focuses on the influence of microblogging reveiws on stock market individual investors,the findings will enrich the theories in information adoption of social media users,and meanwhile it provides theoretical foundation and methodological guidance employed by publicly listed companies to conduct an efficient surveillance on social media and mass opinions.Based on the study findings,the publicly listed companies can identify the key influential factors on the decision-making of invidiual investors,and also conduct a realtime surveillance on microblogging posts which might lead to stock trading anomalies,and consequenlty design efficient contingent plans in accord with the operatinoal path of microblogging posts.The results can be applied as theoretical foundation for relevant regulatory authorities to supervise the information exchange in microblogging and other virtual investmenting-related communities,and to assist the design of well-evidenced and penetrating surveillance regulations.