The Impact Of Exaggerated Language Style On Crowdfunding Project Financing:Text Mining Methods

Crowdfunding,as a new type of Internet financial model,has become one of the effective ways for many individual entrepreneurs and start-ups to obtain external financing and transform innovative projects into entrepreneurial enterprises.The rapid development of the crowdfunding model has led researchers to focus on the factors that affect the success of their projects.The current research is focused on revealing directly quantifiable factors that influence the successful financing of crowdfunding projects.Text as a carrier for displaying crowdfunding projects,and its expression has an important impact on the overall expression of information,so text expression is an important basis for affecting investment decisions.However,as a typical usergenerated content,the text description of crowdfunding projects lacks in-depth research on its language features.The text analysis of crowdfunding projects is an area that needs urgent research and has both theoretical and practical significance.This paper uses exaggeration as a text index for research,and analyzes the alleviating effect of exaggerated language style in text information disclosure on the asymmetry of crowdfunding information.The exaggerated language style is one of the common information disclosure methods in the asymmetric signal environment,and its effectiveness in the field of online financing has not been systematically studied.A total of 123,872 projects from the well-known foreign crowdfunding platform Kickstarter and 5,112 projects from the well-known domestic crowdfunding platform “Zhongchou” were collected.By selecting and expanding the initial keywords,forming an exaggeration dictionary for the crowdfunding professional field,so as to construct an exaggeration degree index for the entire text,use the degree index value and the crowdfunding project financing results to establish a measurement model,and analyze the financing information disclosure process.The effect of using exaggerated language style on the financing results of crowdfunding projects,and compare the similarities and differences between exaggerated language style in Chinese and English.In addition,in order to further explore the prediction effect of exaggerated language style on the financing results of crowdfunding platforms in the future,this paper builds a prediction model based on empirical research and evaluates the effects of different prediction models according to indicators.The paper found that in different language environments,the exaggerated language style utility in the process of text information disclosure showed strong consistency.The exaggerated style in the title and details showed an inverted U-shaped result on the project financing results,while the exaggerated style in the abstract text is not conducive to better financing results.This shows that in the process of identifying and responding to exaggerated information,investors are affected by the overall higher level of exaggeration of the internet title text,which makes it difficult for investors to identify low-level exaggerated information,while the high level of trust in the detailed text prevents investors from responding quickly,so investors will be temporarily attracted to invest.However,from the overall results,investors have a veto attitude towards this type of information.A high degree of exaggeration will cause investors to be alert and resist.Therefore,the information cannot be effectively disclosed after being exaggerated and distorted,and its information asymmetry mitigation mechanism is no longer valid.In addition,the paper found that when financiers use exaggerated language style in the title text,they can adjust the negative results through continuous information disclosure.This shows that in the process of information disclosure,there is a dependency relationship between the information,and it can affect the existing information disclosure effect.Through the prediction model,it is found that in the Chinese and English environment,the exaggerated language style has improved the ability to predict the performance of crowdfunding projects,but the prediction models of Chinese crowdfunding projects and English crowdfunding projects are quite different.In the English environment,the prediction ability of exaggerated language features is more effective than the prediction ability in the Chinese environment.This paper to quantify the the crowdfunding project text processing,perfect the financial text mining research in the field of Internet,to some extent,can solve the problem of text exaggerated identification,and enriched the mechanisms of asymmetric information in the application of online financing,financing text mining and Internet research and development provides a theoretical support.