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    <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.</abstract>
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%0 Conference Proceedings
%T Entity-level Sentiment Analysis in Contact Center Telephone Conversations
%A Fu, Xue-yong
%A Chen, Cheng
%A Laskar, Md Tahmid Rahman
%A Gardiner, Shayna
%A Hiranandani, Pooja
%A Tn, Shashi Bhushan
%Y Li, Yunyao
%Y Lazaridou, Angeliki
%S Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: Industry Track
%D 2022
%8 December
%I Association for Computational Linguistics
%C Abu Dhabi, UAE
%F fu-etal-2022-entity
%X 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.
%R 10.18653/v1/2022.emnlp-industry.49
%U https://aclanthology.org/2022.emnlp-industry.49/
%U https://doi.org/10.18653/v1/2022.emnlp-industry.49
%P 484-491

Markdown (Informal)

[Entity-level Sentiment Analysis in Contact Center Telephone Conversations](https://aclanthology.org/2022.emnlp-industry.49/) (Fu et al., EMNLP 2022)

• Entity-level Sentiment Analysis in Contact Center Telephone Conversations (Fu et al., EMNLP 2022)

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.