The CnOpenData Chinese Financial Text Corpus Database systematically collects financial text data from over 400 authoritative sources nationwide, with a cumulative volume exceeding 110 million records. It encompasses core fields including headlines, full-text content, and precise publication timestamps. Through scientific multi-source collection and standardized processing, this database establishes a comprehensive financial language resource repository spanning multiple platforms, time periods, and themes, providing panoramic data support for observing information flows and linguistic characteristics in China's capital markets.

Key Features:

• Data Distinctiveness: Integrates unstructured texts scattered across various financial information platforms, transforming fragmented information into structured research materials, thereby addressing the gap in large-scale standardized corpora within the financial domain.
• Data Comprehensiveness: Provides continuous longitudinal coverage for long-term textual evolution analysis; encompasses both macro-level policy interpretations and micro-level corporate dynamics in content dimensions.
• Data Reliability: Implements a quality filtration system through source weighting evaluation and cross-verification mechanisms to ensure academic citation value.

Potential Application Scenarios:

• Academic Research: Supports cutting-edge studies such as financial sentiment analysis, media attention measurement, and information disclosure effects; serves as training foundation for computational linguistics, domain-specific lexicon construction, and semantic evolution modeling.
• Commercial Services: Enables alternative data factor development for quantitative investment strategies; facilitates public opinion monitoring modules in corporate competitive intelligence systems; provides underlying intelligent semantic understanding support for fintech products.
• Policy Optimization: Assists regulators in comprehending market information dissemination patterns; establishes benchmarks for policy text effectiveness evaluation; reveals systemic risk transmission pathways through large-scale semantic network analysis.

  By systematically integrating publicly available textual resources in China's financial sector, this database constructs a linguistic observation infrastructure with both breadth and depth. Its standardized structure and multi-dimensional attributes provide a reliable data foundation for interdisciplinary research, demonstrating significant value in advancing innovative applications of text analysis technologies within the financial domain.

Time Coverage

Up to September 2025 (real-time updates)

Field Specifications

Sample Data

Data Update Frequency

Real-time updates