Entity-level Sentiment Analysis in Contact Center Telephone Conversations
Xue-yong Fu, Cheng Chen, Md Tahmid Rahman Laskar, Shayna Gardiner, Pooja Hiranandani, Shashi Bhushan Tn
Abstract
Entity-level sentiment analysis predicts the sentiment about entities mentioned in a given text. It is very useful in a business context to understand user emotions towards certain entities, such as products or companies. In this paper, we demonstrate how we developed an entity-level sentiment analysis system that analyzes English telephone conversation transcripts in contact centers to provide business insight. We present two approaches, one entirely based on the transformer-based DistilBERT model, and another that uses a neural network supplemented with some heuristic rules.- Anthology ID:
- 2022.emnlp-industry.49
- Volume:
- Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: Industry Track
- Month:
- December
- Year:
- 2022
- Address:
- Abu Dhabi, UAE
- Venue:
- EMNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 484–491
- Language:
- URL:
- https://aclanthology.org/2022.emnlp-industry.49
- DOI:
- Cite (ACL):
- Xue-yong Fu, Cheng Chen, Md Tahmid Rahman Laskar, Shayna Gardiner, Pooja Hiranandani, and Shashi Bhushan Tn. 2022. Entity-level Sentiment Analysis in Contact Center Telephone Conversations. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: Industry Track, pages 484–491, Abu Dhabi, UAE. Association for Computational Linguistics.
- Cite (Informal):
- Entity-level Sentiment Analysis in Contact Center Telephone Conversations (Fu et al., EMNLP 2022)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/2022.emnlp-industry.49.pdf