Earticle

초록

영어

In the context of the COVID-19 pandemic Information and communication technologies (ICTs) have emerged as the critical enabler, almost all social activity and shopping is done online. Therefore, online customer reviews (OCRs) have a great impact on customers' purchase decision-making process. Since some companies or sellers strategically create fake online reviews in an effort to influence customers' purchase decisions, the detection of fake (deception) plays a critical role in e-commerce. However, researchers in fake review detection faced a lot of problems. One of them is the lack of a high-quality fake review dataset. The purpose of our research is to study fake reviews' features based on a publicly available dataset and test different machine learning methods for detecting fake reviews through analyzing sentiments and readability.

목차

Abstract
Introduction
Methods
Results and Conclusion
References

저자

• Olga Chernyaeva [ Pusan National University, College of Business Administration ]
• Taeho Hong [ Pusan National University, College of Business Administration ]

참고문헌