TY  - JOUR
T1  - Online Opinion Fraud Detection Using Graph Neural Network
AU  - Hyun, Woochang 
AU  - Lee, Insoo 
AU  - Suh, Bongwon 
JO  - Journal of KIISE, JOK
PY  - 2023
DA  - 2023/1/14
DO  - 10.5626/JOK.2023.50.11.985
KW  - opinion fraud
KW  - fraud detection
KW  - graph neural network
KW  - interpretability
AB  - This study proposed a graph neural network model to detect opinion frauds that undermine the of information and hinder users" decision-making on online platforms. The proposed method uses methods on a graph of relationships between online reviews to produce relational representations, are then combined with the characteristics of the center nodes to predict fraud. Experimental results on a real-world dataset demonstrate that this approach is more accurate and faster than existing state-of-art methods, while also providing interpretability for key relations. With the help of this study, practitioners will be able to utilize the analytical results in decision-making and overcome the general drawback of neural network-based models" lack of explainability.