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Application of Machine Learning Algorithms in Predicting Social-Planning Platform Donations

  • Author(s): Kim, Daehyun
  • Advisor(s): Wu, Yingnian
  • et al.
Abstract

Pledgeling is a platform that powers corporate giving and social impact programs for busi-

nesses of all sizes by integrating donation features in the backend. One of Pledgeling's part-

ners is Evite, the world's leading digital platform for bringing people together with event

invitations. In this study, the data from Pledgeling is used to train a logistic regression

model to determine which aspects of RSVP events lead to hosts turning on the donation

features. From the rst study, it was statistically signicant that categories of events that

fall into Organizations, Weddings, and Animals were more likely to add donation features.

Also events from the West and Northeast regions during Q1 and Q4 during the calender

year were more likely to add donation features. Additionally, data is used to train a linear

regression model to study which features lead to users donating more for each event. From

the second study, there were statistically signicant results that categories of events that fall

into Organizations, Weddings, and Get Togethers were donating more money. Also, results

indicated that events in West and Northeast regions were donating more from the beginning

of summer to the end of the year. Lastly, events donated more to Science-related as well as

Public Health-related causes compared to causes for Animals organizations.

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