mlsanityData to 14 Oct 2026

FinEntity: Entity-level Sentiment Classification for Financial Texts

arXiv 2310.12406 ↗First posted 19 Oct 2023cs.CLcited by 14

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Abstract (arXiv)

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 urlhttps://github.com/yixuantt/FinEntity

Key facts. Cited by 14 papers in the map (data through 14 Oct 2026). Builds on 10 of its 23 references that are in the map. First posted on arXiv 19 Oct 2023.

Builds on

10 of 23 references.

References · 10

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2019HuggingFace's Transformers: State-of-the-art Natural Language Processingcited by 2,218
  3. 2013Good Debt or Bad Debt: Detecting Semantic Orientations in Economic Textscited by 310
  4. 2020FinBERT: A Pretrained Language Model for Financial Communicationscited by 161
  5. 2023InvestLM: A Large Language Model for Investment using Financial Domain Instruction Tuningcited by 82
  6. 2020Impact of News on the Commodity Market: Dataset and Resultscited by 80
  7. 2023Trillion Dollar Words: A New Financial Dataset, Task & Market Analysiscited by 75
  8. 2023SEntFiN 1.0: Entity-Aware Sentiment Analysis for Financial Newscited by 18
  9. 2023FiNER-ORD: Financial Named Entity Recognition Open Research Datasetcited by 17
  10. 2023Financial Numeric Extreme Labelling: A Dataset and Benchmarking for XBRL Taggingcited by 12

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 6; 2025: 7; 2026: 1.

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  1. 2024Designing Heterogeneous LLM Agents for Financial Sentiment Analysiscited by 48
  2. 2024Beyond Surface Similarity: Detecting Subtle Semantic Shifts in Financial Narrativescited by 13
  3. 2024Deciphering Political Entity Sentiment in News with Large Language Models: Zero-Shot and Few-Shot Strategiescited by 8
  4. 2024SubjECTive-QA: Measuring Subjectivity in Earnings Call Transcripts' QA Through Six-Dimensional Feature Analysiscited by 8
  5. 2024EFSA: Towards Event-Level Financial Sentiment Analysiscited by 7
  6. 2025Entity Framing and Role Portrayal in the Newscited by 6
  7. 2025Bridging Language Models and Financial Analysiscited by 4
  8. 2025Finance Language Model Evaluation (FLaME)cited by 4
  9. 2025Language Modeling for the Future of Finance: A Survey into Metrics, Tasks, and Data Opportunitiescited by 3
  10. 2025LongEmotion: Measuring Emotional Intelligence of Large Language Models in Long-Context Interactioncited by 3
  11. 2026A Scalable Entity-Based Framework for Auditing Bias in Large Language Modelscited by 2
  12. 2025Factor Augmented Supervised Learning with Text Embeddingscited by 1
2 more
  1. 2024SILC-EFSA: Self-aware In-context Learning Correction for Entity-level Financial Sentiment Analysiscited by 0
  2. 2025Interpreting Fedspeak with Confidence: A LLM-Based Uncertainty-Aware Framework Guided by Monetary Policy Transmission Pathscited by 0