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        <title>FinEntity: Entity-level Sentiment Classification for Financial Texts</title>
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    <abstract>In the financial domain, conducting entity-level sentiment analysis is crucial for accurately assessing the sentiment directed toward a specific financial entity. To our knowledge, no publicly available dataset currently exists for this purpose. In this work, we introduce an entity-level sentiment classification dataset, called FinEntity, that annotates financial entity spans and their sentiment (positive, neutral, and negative) in financial news. We document the dataset construction process in the paper. Additionally, we benchmark several pre-trained models (BERT, FinBERT, etc.) and ChatGPT on entity-level sentiment classification. In a case study, we demonstrate the practical utility of using FinEntity in monitoring cryptocurrency markets. The data and code of FinEntity is available at https://github.com/yixuantt/FinEntity.</abstract>
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%0 Conference Proceedings
%T FinEntity: Entity-level Sentiment Classification for Financial Texts
%A Tang, Yixuan
%A Yang, Yi
%A Huang, Allen
%A Tam, Andy
%A Tang, Justin
%Y Bouamor, Houda
%Y Pino, Juan
%Y Bali, Kalika
%S Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
%D 2023
%8 December
%I Association for Computational Linguistics
%C Singapore
%F tang-etal-2023-finentity
%X In the financial domain, conducting entity-level sentiment analysis is crucial for accurately assessing the sentiment directed toward a specific financial entity. To our knowledge, no publicly available dataset currently exists for this purpose. In this work, we introduce an entity-level sentiment classification dataset, called FinEntity, that annotates financial entity spans and their sentiment (positive, neutral, and negative) in financial news. We document the dataset construction process in the paper. Additionally, we benchmark several pre-trained models (BERT, FinBERT, etc.) and ChatGPT on entity-level sentiment classification. In a case study, we demonstrate the practical utility of using FinEntity in monitoring cryptocurrency markets. The data and code of FinEntity is available at https://github.com/yixuantt/FinEntity.
%R 10.18653/v1/2023.emnlp-main.956
%U https://aclanthology.org/2023.emnlp-main.956
%U https://doi.org/10.18653/v1/2023.emnlp-main.956
%P 15465-15471

Markdown (Informal)

[FinEntity: Entity-level Sentiment Classification for Financial Texts](https://aclanthology.org/2023.emnlp-main.956) (Tang et al., EMNLP 2023)

• FinEntity: Entity-level Sentiment Classification for Financial Texts (Tang et al., EMNLP 2023)

ACL

• Yixuan Tang, Yi Yang, Allen Huang, Andy Tam, and Justin Tang. 2023. FinEntity: Entity-level Sentiment Classification for Financial Texts. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pages 15465–15471, Singapore. Association for Computational Linguistics.