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Financial News Headline Sentiment
LLM Fine-Tuning Data
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Free
About
This dataset is designed for sentiment analysis of financial news headlines, offering insights from the perspective of a retail investor. Its core purpose is to provide a basis for understanding the sentiment (negative, neutral, or positive) expressed within economic texts.
Columns
The dataset contains two primary columns:
- Sentiment: This column indicates the emotional tone of the news headline, categorised as negative, neutral, or positive.
- News Headline: This column contains the actual financial news headline text for analysis.
Distribution
The data files are provided in text (.txt) format, although data files are typically in CSV format. The dataset is organised into several files based on the level of agreement in sentiment annotation, including
Sentences_50Agree.txt (671.36 KB), Sentences_66Agree.txt (580.25 KB), Sentences_75Agree.txt (466.99 KB), and Sentences_AllAgree.txt (299.64 KB). The total number of rows or records is not explicitly stated, but the file sizes indicate the volume of data.Usage
This dataset is ideal for various applications, including:
- Learning about sentiment analysis techniques and natural language processing.
- Research into financial linguistics and market sentiment.
- General application development where financial news sentiment is relevant.
- LLM Fine-Tuning to enhance language models with financial sentiment understanding.
Coverage
The dataset focuses on financial news headlines. While specific geographic, time range, or demographic scopes are not detailed, it is designed for the perspective of a retail investor. The dataset is static and has an expected update frequency of 'Never', with the last update noted as five years ago.
License
CC BY-NC-SA 4.0.
Who Can Use It
This dataset is particularly suitable for:
- Researchers studying financial markets, sentiment analysis, or natural language processing.
- Data Scientists and Machine Learning Engineers developing models for sentiment prediction or text classification.
- Students learning about data analysis, machine learning, and financial applications.
- Anyone interested in understanding retail investor sentiment from financial news.
Dataset Name Suggestions
- Financial News Headline Sentiment
- Retail Investor Financial Sentiment
- FinancialPhraseBank Sentiment Data
- Economic Text Sentiment Analysis
- Financial News Sentiment Bank
Attributes
Original Data Source: Financial News Headline Sentiment
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