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arXiv · 2501.04959

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

Wonseong Kim·Christina Niklaus·Choong Lyol Lee·Siegfried Handschuh
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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.

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Wonseong Kim, Christina Niklaus, Choong Lyol Lee, Siegfried Handschuh. 2025-01-09. DisSim-FinBERT: Text Simplification for Core Message Extraction in Complex Financial Texts. https://arxiv.org/abs/2501.04959

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