Textual Content Moderation in C2C Marketplace

Yusuke Shido, Hsien-Chi Liu, Keisuke Umezawa


Abstract
Automatic monitoring systems for inappropriate user-generated messages have been found to be effective in reducing human operation costs in Consumer to Consumer (C2C) marketplace services, in which customers send messages directly to other customers.We propose a lightweight neural network that takes a conversation as input, which we deployed to a production service.Our results show that the system reduced the human operation costs to less than one-sixth compared to the conventional rule-based monitoring at Mercari.
Anthology ID:
2022.ecnlp-1.8
Volume:
Proceedings of the Fifth Workshop on e-Commerce and NLP (ECNLP 5)
Month:
May
Year:
2022
Address:
Dublin, Ireland
Venue:
ECNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
58–62
Language:
URL:
https://aclanthology.org/2022.ecnlp-1.8
DOI:
10.18653/v1/2022.ecnlp-1.8
Bibkey:
Cite (ACL):
Yusuke Shido, Hsien-Chi Liu, and Keisuke Umezawa. 2022. Textual Content Moderation in C2C Marketplace. In Proceedings of the Fifth Workshop on e-Commerce and NLP (ECNLP 5), pages 58–62, Dublin, Ireland. Association for Computational Linguistics.
Cite (Informal):
Textual Content Moderation in C2C Marketplace (Shido et al., ECNLP 2022)
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PDF:
https://aclanthology.org/2022.ecnlp-1.8.pdf
Video:
 https://aclanthology.org/2022.ecnlp-1.8.mp4