Predicting the Level of Crowdfunding Outcome in Africa A Supervised Machine Learning Approach

One crucial challenge of crowdfunding is that it is hard for fundraisers and backers to anticipate the outcome of crowdfunding campaigns. Across platforms, many crowdfunding campaigns fail to achieve their funding goal. Hence, studies focusing of the outcome of crowdfunding is also growing. In this study, we implement a supervised machine learning methodology to investigate the determinants of the level of crowdfunding with emphasis on Africa. The statistical methods used in the study produced a high prediction accuracy. Irrespective of the method used, the number of backers is identified to be the most important predictor of the level of funding. Also, the average amount pledged to the project and the duration of the project are important features that predict the level of funding. 

by Isaac Okyere Paintsil | Zhao Xicang | Oliver Joseph Abban "Predicting the Level of Crowdfunding Outcome in Africa: A Supervised Machine Learning Approach" 

Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, 

URL: https://www.ijtsrd.compapers/ijtsrd42539.pdf 

Paper URL: https://www.ijtsrd.comeconomics/finance/42539/predicting-the-level-of-crowdfunding-outcome-in-africa-a-supervised-machine-learning-approach/isaac-okyere-paintsil

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