TY - JOUR
T1 - Hybrid Fraud Detection Model
T2 - Detecting Fraudulent Information in the Healthcare Crowdfunding
AU - Choi, Jaewon
AU - Kim, Jaehyoun
AU - Lee, Ho
N1 - Publisher Copyright:
© 2022 KSII
PY - 2022/3/31
Y1 - 2022/3/31
N2 - In the crowdfunding market, various crowdfunding platforms can offer founders the possibilities to collect funding and launch someone’s next campaign, project or events. Especially, healthcare crowdfunding is a field that is growing rapidly on health-related problems based on online platforms. One of the largest platforms, GoFundMe, has raised US$ 5 billion since 2010. Unfortunately, while providing crucial help to care for many people, it is also increasing risk of fraud. Using the largest platform of crowdfunding market, GoFundMe, we conduct an exhaustive search of detection on fraud from October 2016 to September 2019. Data sets are based on 6 main types of medical focused crowdfunding campaigns or events, such as cancer, in vitro fertilization (IVF), leukemia, health insurance, lymphoma and, surgery type. This study evaluated a detect of fraud process to identify fraud from non-fraud healthcare crowdfunding campaigns using various machine learning technics.
AB - In the crowdfunding market, various crowdfunding platforms can offer founders the possibilities to collect funding and launch someone’s next campaign, project or events. Especially, healthcare crowdfunding is a field that is growing rapidly on health-related problems based on online platforms. One of the largest platforms, GoFundMe, has raised US$ 5 billion since 2010. Unfortunately, while providing crucial help to care for many people, it is also increasing risk of fraud. Using the largest platform of crowdfunding market, GoFundMe, we conduct an exhaustive search of detection on fraud from October 2016 to September 2019. Data sets are based on 6 main types of medical focused crowdfunding campaigns or events, such as cancer, in vitro fertilization (IVF), leukemia, health insurance, lymphoma and, surgery type. This study evaluated a detect of fraud process to identify fraud from non-fraud healthcare crowdfunding campaigns using various machine learning technics.
KW - Collaborative Filtering
KW - Crowdfunding
KW - Fraud Detection
KW - LDA
KW - Social SVD
UR - https://www.scopus.com/pages/publications/85127989694
U2 - 10.3837/tiis.2022.03.014
DO - 10.3837/tiis.2022.03.014
M3 - Article
AN - SCOPUS:85127989694
SN - 1976-7277
VL - 16
SP - 1006
EP - 1027
JO - KSII Transactions on Internet and Information Systems
JF - KSII Transactions on Internet and Information Systems
IS - 3
ER -