Supervised Learning Model for Kickstarter Campaigns With R Mining

International Journal of Information Technology, Modeling and Computing (IJITMC) Vol. 4, No.1, February 2016

12 Pages Posted: 3 Feb 2020

See all articles by R. S. Kamath

R. S. Kamath

Chhatrapati Shahu Institute of Business Education

R. K. Kamat

Shivaji University

Date Written: 2016

Abstract

Web mediated crowd funding is a talented paradigm used by project launcher to solicit funds from backers to realize projects. Kickstarter is one such largest funding platform for creative projects. However, not all the campaigns in Kickstarter attain their funding goal and are successful. It is therefore important to know about campaigns’ chances of success. As a broad goal, authors intended in extraction of the hidden knowledge from the Kickstarter campaign database and classification of these projects based on their dependency parameters. For this authors have designed a classification model for the analysis of Kickstarter campaigns by using direct information retrieved from Kickstarter URLs. This aids to identify the possibility of success of a campaign.

Keywords: crowd funding; prediction; classifiers; machine learning; R systems; kickstarter

Suggested Citation

Kamath, R. S. and Kamat, R. K., Supervised Learning Model for Kickstarter Campaigns With R Mining (2016). International Journal of Information Technology, Modeling and Computing (IJITMC) Vol. 4, No.1, February 2016, Available at SSRN: https://ssrn.com/abstract=3513341 or http://dx.doi.org/10.2139/ssrn.3513341

R. S. Kamath (Contact Author)

Chhatrapati Shahu Institute of Business Education

Kolhapur
India

R. K. Kamat

Shivaji University

Kolhapur
416004
India

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
202
Abstract Views
807
Rank
272,294
PlumX Metrics