Commodities Industries Intelligence

Bitvore's Commodities Industries Intelligence offers in-depth insights into the world of commodities industries such as raw materials, chemicals, and construction materials. Navigate the market with data on supply chain dynamics, production rates, and materials innovations.

Key Benefits:

- Informed Decisions: The latest intelligence on Commodities companies, market shifts, sustainability trends, emerging hotspots, potential risk zones, regulatory changes, industry sentiments and much more.

- Deep Dive Analysis: Comprehensive coverage of 168 Finance Topics and 37 unique ESG Topics, all filtered to spotlight the Commodities sector.

- Broad Data Coverage: Monitor 60k+ quality global sources, using publicly available and premium licensed data, tracking developments related to over 150,000 global Commodities companies, both public and private.

Bitvore powers data-driven actionable signals through advanced, trusted and proven AI & ML processes, enabling our customers to manage risks and identify opportunities. Our NLP and ML models analyze unstructured content and are trained to identify 17 Finance Topics (with 151 Sub Topics) and 37 unique ESG material topics (tied to SASB, the Big 4 and other taxonomies). 60k+ quality globally sources monitored for 400k+ companies globally, using publicly available and premium licensed data. Bitvore delivers timely data, insights, signals and indicators of significant developments affecting companies, industries, bonds, markets and emerging themes including Bitvore Risk, Growth, ESG, E, S and G entity and article level sentiment scores.

Some sample tables are included below:

- ORGS: Contains data on organizations, which represent corporate entities, companies or organizations both public and private
- RECORD: a table of articles about corporate entities, companies or organizations both public and private.
- SIGNALS: Contains data about topics that are identified for any given company

Some Sample fields from the RECORD table are included below:

- ARTICLETYPE: Type of the record, News or Press Release.
- SENTIMENT: Overall Sentiment of the record within a range of -1.0 (negative) and 1.0 (positive).
- SOURCENAME: Name (typically hostname) of the source of the record.
- ESGSENTIMENT: ESG Sentiment of the record within a range of -1.0 (negative) and 1.0 (positive).
- SOURCEURL: URL for the source of the record.
- KEY: 56 character unique identifier of the data record, a record may be on multiple rows if more than one company is associated with it.
- PUBLISHED_DATE: Date/time the record was initially published at as yyyy-MM-dd hh:mm.
- BODY: Body of any specified article
- TITLE: Title of any specified article

Some Sample fields from the ORGS table are included below:

- ID: Bitvore ID that uniquely identifies the company
- STATE: State code of the state the company’s headquarters is located in
- EMPLOYEES: Number of employees for the company within a range.
- TICKER: An abbreviation used to uniquely identify publicly traded companies
- COUNTRY: Country the company’s headquarters is located in
- LASTMODIFIED: The date a record was last changed as yyy-MM-dd hh:mm. It’s not often but on occasion a record can be changed to reflect either new information extracted from it or improvements to models to get more accurate information, such as a sentiment value.

Bitvore Commodities Intelligence Data Sets also include “Layer 2” advanced tags for industries, people, keywords/phrases, relationships, and geography providing programmatic access to complex values and relationships.

Industries – 3 layered hierarchy of Economic Sector > Industry Group > Business Sector

People – 2.55 million plus database of reference data with accurate extraction and disambiguation

Keywords/Phrases – Broad lexicon of useful text tied to conceptual meaning, scored by confidence and salience

Relationships – Over 17 different types of NLP-derived relationships like Person-Title-Company or Subsidiary-of with scored evidence

Geography – Bottom-up tagging of geographical references including named places and latitude/longitude mapping

Sentiment – Per-entity and per use sentiment scoring specific to references/co-references

Sentiment Scores - Bitvore Risk, Growth, ESG, E, S and G entity and article level sentiment scores.

搜集汇总

背景与挑战

背景概述

该数据集提供大宗商品行业的深度情报分析，涵盖供应链、生产率和创新数据，包含16.8万金融主题和37个ESG主题的全面分析。通过AI技术监测全球6万多个数据源，跟踪超过15万家公司的动态，并提供实体和文章层面的情感评分。