Fine-Grained Argument Understanding with BERT Ensemble Techniques: A Deep Dive into Financial Sentiment Analysis

Eugene Sy, Tzu Cheng Peng, Shih Hsuan Huang, Hen You Lin, Yung Chun Chang

研究成果: 書貢獻/報告類型會議貢獻

1 引文 斯高帕斯(Scopus)

摘要

While argument mining has garnered attention over the years, its application in the financial sector remains nascent. This study presents a BERT-based ensemble learning approach tailored for sentiment analysis grounded in financial narratives, specifically focusing on unearthing arguments. For a nuanced analysis, we dissect the challenge into two pivotal subtasks using earnings conference call data: (1) Argument Unit Classification, and (2) Argument Relation Detection and Classification. Experimental results substantiate that our approach not only effectively forecasts both tasks but also outperforms the comparisons and achieve SOTA performance. This underscores the potential of our method in fine-grained argument understanding within financial analysis.
原文英語
主出版物標題ROCLING 2023 - Proceedings of the 35th Conference on Computational Linguistics and Speech Processing
編輯Jheng-Long Wu, Ming-Hsiang Su, Hen-Hsen Huang, Yu Tsao, Hou-Chiang Tseng, Chia-Hui Chang, Lung-Hao Lee, Yuan-Fu Liao, Wei-Yun Ma
發行者The Association for Computational Linguistics and Chinese Language Processing (ACLCLP)
頁面242-249
頁數8
ISBN(電子)9789869576963
出版狀態已發佈 - 2023
事件35th Conference on Computational Linguistics and Speech Processing, ROCLING 2023 - Taipei City, 台灣
持續時間: 10月 20 202310月 21 2023

出版系列

名字ROCLING 2023 - Proceedings of the 35th Conference on Computational Linguistics and Speech Processing

會議

會議35th Conference on Computational Linguistics and Speech Processing, ROCLING 2023
國家/地區台灣
城市Taipei City
期間10/20/2310/21/23

ASJC Scopus subject areas

  • 語言與語言學
  • 言語和聽力

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