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DisSim-FinBERT: Text Simplification for Core Message Extraction in Complex Financial Texts

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  • Wonseong Kim
  • Christina Niklaus
  • Choong Lyol Lee
  • Siegfried Handschuh

Abstract

This study proposes DisSim-FinBERT, a novel framework that integrates Discourse Simplification (DisSim) with Aspect-Based Sentiment Analysis (ABSA) to enhance sentiment prediction in complex financial texts. By simplifying intricate documents such as Federal Open Market Committee (FOMC) minutes, DisSim improves the precision of aspect identification, resulting in sentiment predictions that align more closely with economic events. The model preserves the original informational content and captures the inherent volatility of financial language, offering a more nuanced and accurate interpretation of long-form financial communications. This approach provides a practical tool for policymakers and analysts aiming to extract actionable insights from central bank narratives and other detailed economic documents.

Suggested Citation

  • Wonseong Kim & Christina Niklaus & Choong Lyol Lee & Siegfried Handschuh, 2025. "DisSim-FinBERT: Text Simplification for Core Message Extraction in Complex Financial Texts," Papers 2501.04959, arXiv.org, revised Mar 2025.
    • Handle: RePEc:arx:papers:2501.04959
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    References listed on IDEAS

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