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Predicting outcomes in crowdfunding campaigns with textual, visual, and linguistic signals
2020
This paper introduces a neural network and natural language processing approach to predict the outcome of crowdfunding startup pitches using text, speech, and video metadata in 20,188 crowdfunding campaigns. Our study emphasizes the need to understand crowdfunding from an investor's perspective. Linguistic styles in crowdfunding campaigns that aim to trigger excitement or are aimed at inclusiveness are better predictors of campaign success than firm-level determinants. At the contrary, higher
doi:10.24451/arbor.11978
fatcat:k6be3wjbz5hnhal3dietc2ncr4