Linguistic information distortion on investment decision-making in the crowdfunding market

Purpose: Information distortion affects the perception of quality, which, in turn, influences investment decisions and determines the pledge results of fundraising. This study combines signalling theory with persuasion theory to empirically study the effects of linguistic information distortion from fraudulent cues on a crowdfunding campaign's fundraising outcomes using text analytics, with implications for entrepreneurs, platforms and investors. Design/methodology/approach: This study empirically analyzes 328,974 crowdfunding projects from the Kickstarter platform. Information distortion is detected using four indicators, based on text mining analytics. An econometric model is built to estimate the impact of information distortion, while the predictive power of the information distortion is detected through machine learning. Findings: The results inform that distortion in the blurb, detailed description and reward statement dampen a campaign's success, but embellishing the entrepreneur's biography enhances the success of financing. Furthermore, information distortion exhibits a significant inverted U-shaped influence. The effect of the interaction terms suggests that campaigns with high pledge goals are more sensitive to information distortion, and that native-speaking entrepreneurs are adept at applying linguistic skills to promote the campaign. Originality/value: This study provides a linguistic method to detect the influence of information distortion on crowdfunding campaigns. Further, the study offers some practical suggestions for entrepreneurs on how to generate attractive narratives, and contributes to the investor's decision-making and informs the platform's promotion strategy.