Predicting Fundraising Performance in Medical Crowdfunding Campaigns Using Machine Learning
The coronavirus disease (COVID-19) pandemic has flooded public health organizations around the world, highlighting the significance and responsibility of medical crowdfunding in filling a series of gaps and shortcomings in the publicly funded health system and providing a new fundraising solution fo...
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doaj-2934cbd2bb554728a673b30f6db542da2021-01-12T00:03:12ZengMDPI AGElectronics2079-92922021-01-011014314310.3390/electronics10020143Predicting Fundraising Performance in Medical Crowdfunding Campaigns Using Machine LearningNianjiao Peng0Xinlei Zhou1Ben Niu2Yuanyue Feng3College of Management, Shenzhen University, Shenzhen 518061, ChinaCollege of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518061, ChinaCollege of Management, Shenzhen University, Shenzhen 518061, ChinaCollege of Management, Shenzhen University, Shenzhen 518061, ChinaThe coronavirus disease (COVID-19) pandemic has flooded public health organizations around the world, highlighting the significance and responsibility of medical crowdfunding in filling a series of gaps and shortcomings in the publicly funded health system and providing a new fundraising solution for people that addresses health-related needs. However, the fact remains that medical fundraising from crowdfunding sources is relatively low and only a few studies have been conducted regarding this issue. Therefore, the performance predictions and multi-model comparisons of medical crowdfunding have important guiding significance to improve the fundraising rate and promote the sustainable development of medical crowdfunding. Based on the data of 11,771 medical crowdfunding campaigns from a leading donation-based platform called Weibo Philanthropy, machine-learning algorithms were applied. The results demonstrate the potential of ensemble-based machine-learning algorithms in the prediction of medical crowdfunding project fundraising amounts and leave some insights that can be taken into consideration by new researchers and help to produce new management practices.https://www.mdpi.com/2079-9292/10/2/143crowdfundingmedical crowdfundingmachine learningfundraising predictionweibo philanthropy |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Nianjiao Peng Xinlei Zhou Ben Niu Yuanyue Feng |
spellingShingle |
Nianjiao Peng Xinlei Zhou Ben Niu Yuanyue Feng Predicting Fundraising Performance in Medical Crowdfunding Campaigns Using Machine Learning Electronics crowdfunding medical crowdfunding machine learning fundraising prediction weibo philanthropy |
author_facet |
Nianjiao Peng Xinlei Zhou Ben Niu Yuanyue Feng |
author_sort |
Nianjiao Peng |
title |
Predicting Fundraising Performance in Medical Crowdfunding Campaigns Using Machine Learning |
title_short |
Predicting Fundraising Performance in Medical Crowdfunding Campaigns Using Machine Learning |
title_full |
Predicting Fundraising Performance in Medical Crowdfunding Campaigns Using Machine Learning |
title_fullStr |
Predicting Fundraising Performance in Medical Crowdfunding Campaigns Using Machine Learning |
title_full_unstemmed |
Predicting Fundraising Performance in Medical Crowdfunding Campaigns Using Machine Learning |
title_sort |
predicting fundraising performance in medical crowdfunding campaigns using machine learning |
publisher |
MDPI AG |
series |
Electronics |
issn |
2079-9292 |
publishDate |
2021-01-01 |
description |
The coronavirus disease (COVID-19) pandemic has flooded public health organizations around the world, highlighting the significance and responsibility of medical crowdfunding in filling a series of gaps and shortcomings in the publicly funded health system and providing a new fundraising solution for people that addresses health-related needs. However, the fact remains that medical fundraising from crowdfunding sources is relatively low and only a few studies have been conducted regarding this issue. Therefore, the performance predictions and multi-model comparisons of medical crowdfunding have important guiding significance to improve the fundraising rate and promote the sustainable development of medical crowdfunding. Based on the data of 11,771 medical crowdfunding campaigns from a leading donation-based platform called Weibo Philanthropy, machine-learning algorithms were applied. The results demonstrate the potential of ensemble-based machine-learning algorithms in the prediction of medical crowdfunding project fundraising amounts and leave some insights that can be taken into consideration by new researchers and help to produce new management practices. |
topic |
crowdfunding medical crowdfunding machine learning fundraising prediction weibo philanthropy |
url |
https://www.mdpi.com/2079-9292/10/2/143 |
work_keys_str_mv |
AT nianjiaopeng predictingfundraisingperformanceinmedicalcrowdfundingcampaignsusingmachinelearning AT xinleizhou predictingfundraisingperformanceinmedicalcrowdfundingcampaignsusingmachinelearning AT benniu predictingfundraisingperformanceinmedicalcrowdfundingcampaignsusingmachinelearning AT yuanyuefeng predictingfundraisingperformanceinmedicalcrowdfundingcampaignsusingmachinelearning |
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