Difference between revisions of "Predicting Donations in Ukraine Crowdfunding Projects"

Revision as of 14:42, 11 March 2022

Title: Predicting Donations in Ukraine Crowdfunding Projects Mentor: Dr. Larry Zhiming Xu

Approach: Data from Ukraine crowdfunding projects will be obtained to explore what factors contribute to donations. Natural language processing, network analysis, and other methods will be used to examine public sentiment, linguistic traces, and network structures that facilitate or hinder fundraising.

Summary: Crowdfunding has been playing an important role in the ongoing Ukraine crisis. To date, Ukrainian NGOs, humanitarian groups, and civilians have received a flood of cash and crypto donations from a variety of crowdfunding projects launched across the globe. These fundraising projects, which are usually publicly visible, include valuable information about fundraising strategies and money flow networks. Hence, they allow for the close examination of the specific structures, processes, and mechanisms through which donations are attracted globally.

Student activities: The REU fellows will perform the following major tasks: 1) Retrieving data from publicly available webpages; 2) Preparing data for appropriate analysis; 3) Assisting in performing the analysis on a large text corpus consisting of crowdfunding project descriptions; 4) Getting familiar with analytical procedures such as sentiment analysis, topic modeling, and network analysis; 5) Getting familiar with corresponding data visualization tools and techniques. 6) Assisting in writing academic articles.

Student background: Students should be familiar with web scraping/crawling techniques and can retrieve and store unstructured data from the web. Basic knowledge of natural language processing and network analysis is helpful but is not necessary.