Can You Distinguish Truthful from Fake Reviews? User Analysis and Assistance Tool for Fake Review Detection

Jeonghwan Kim, Junmo Kang, Suwon Shin, Sung-Hyon Myaeng


Abstract
Customer reviews are useful in providing an indirect, secondhand experience of a product. People often use reviews written by other customers as a guideline prior to purchasing a product. Such behavior signifies the authenticity of reviews in e-commerce platforms. However, fake reviews are increasingly becoming a hassle for both consumers and product owners. To address this issue, we propose You Only Need Gold (YONG), an essential information mining tool for detecting fake reviews and augmenting user discretion. Our experimental results show the poor human performance on fake review detection, substantially improved user capability given our tool, and the ultimate need for user reliance on the tool.
Anthology ID:
2021.hcinlp-1.9
Volume:
Proceedings of the First Workshop on Bridging Human–Computer Interaction and Natural Language Processing
Month:
April
Year:
2021
Address:
Online
Venues:
EACL | HCINLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
53–59
Language:
URL:
https://aclanthology.org/2021.hcinlp-1.9
DOI:
Bibkey:
Cite (ACL):
Jeonghwan Kim, Junmo Kang, Suwon Shin, and Sung-Hyon Myaeng. 2021. Can You Distinguish Truthful from Fake Reviews? User Analysis and Assistance Tool for Fake Review Detection. In Proceedings of the First Workshop on Bridging Human–Computer Interaction and Natural Language Processing, pages 53–59, Online. Association for Computational Linguistics.
Cite (Informal):
Can You Distinguish Truthful from Fake Reviews? User Analysis and Assistance Tool for Fake Review Detection (Kim et al., HCINLP 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.hcinlp-1.9.pdf