The dataset is built using Accern’s AI Platform to uncover opportunities and risks hidden around the Economic, Social and Governance (ESG) behavior of a company. The ESG signals are detected from massive volumes of unstructured content from a global collection of public news and blog outlets. Metrics: - History from Dec 2014 - US Companies - Companies are mapped using Bloomberg FIGIs and Tickers. **Events and Company coverage can be extended if required** ESG Events Covered: - Environment (EPA, Clean Ecosystem, Carbon Footprint, Climate Change) - Social (Workplace Health & Safety, Human Rights, Community Relations, Misconduct, Civil Society, Labor Union) - Governance (Reorganization, Position, Executive Compensation, Compliance, Corporate Events, Audit Committee) Methodology: Accern's ESG NLP model has been trained to understand the mentions of ESG events in text documents and uses Accern's knowledge graph. The model identifies only highly relevant articles and passages that contain discussions of ESG issues. For each passage, the model then computes an ESG sentiment along with a number of other analytics. Key Fields: entity_name event_relevance event_sentiment event_text harvested_at event event_group doc_url