A Swarm Enhanced Light Gradient Boosting Machine for Crowdfunding Project Outcome Prediction

Shuang Geng, Miaojia Huang, Zhibo Wang

Research output: Chapter in Book/Conference paperConference paperpeer-review


Crowdfunding is an emerging financing method that project founders could obtain funding from vast investors through the online platform. Therefore, investigating the critical features of crowdfunding projects to forecast the project outcomes have become indispensable. This research draws upon some potential factors and introduces a swarm enhanced light gradient boosting machine (S-LightGBM) model to forecast the crowdfunding performance. Text mining and lexicon-based sentiment analysis methods were employed to derive the linguistic and sentiment features of project descriptions. This study compares the predictive power of logistic regression, support vector machine, light gradient boosting machine, and S-LightGBM on 5916 crowdfunding projects between 2017 and 2018. The result shows that the S-LightGBM approach achieves superior accuracy results than conventional methods. The usefulness of linguistic and sentiment features was also investigated and discussed. This research contributes to the existing research on machine learning methods and crowdfunding and provides fundraisers guidance for the presentation and illustration of innovative projects on crowdfunding platforms.
Original languageEnglish
Title of host publicationInternational Conference on Machine Learning for Cyber Security, ML4CS 2020
Subtitle of host publicationThird International Conference, ML4CS 2020 Guangzhou, China, October 8–10, 2020 Proceedings, Part III
EditorsXiaofeng Chen, Hongyang Yan, Qiben Yan, Xiangliang Zhang
Place of PublicationSwitzerland
PublisherSpringer Link
Number of pages11
ISBN (Electronic)9783030624637
ISBN (Print)9783030624620
Publication statusPublished - 11 Nov 2020
Externally publishedYes
Event3rd International Conference on Machine Learning for Cyber Security - Guangzhou, China
Duration: 8 Oct 202010 Oct 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12488 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference3rd International Conference on Machine Learning for Cyber Security
Abbreviated titleML4CS 2020


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