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
- Editors:
- Shervin Malmasi, Oleg Rokhlenko, Nicola Ueffing, Ido Guy, Eugene Agichtein, Surya Kallumadi
- 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
- 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)
- PDF:
- https://preview.aclanthology.org/improve-issue-templates/2022.ecnlp-1.8.pdf