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ESG Sentiment detection

Overview

The ESG Sentiment detector aims at categorizing ESG (Environmental, Social and Governance) news, social media posts or CSR (Corporate Social Responsibility) reports as negative or positive based on the actions or statements attributed to entities like companies, countries or institutions.

The detector also extracts the references to the above entities found in the text along with ESG data plus summary ESG performance data for the whole input document.

Hence, the detector aims at providing the users with an insightful ESG overview of a company, or set of companies, in order to add more context and useful information to structured data, which may be misleading if considered without any further reference.

Categorization

Categorization works in a similar way to document classification and is based on a taxonomy.

Warning

Unlike the API resources dedicated to document classification, this is an information detector and the category tree of its taxonomy is not obtainable with API self-documentation resources like for document classification taxonomies, so it is indicated below.

The category tree includes all of the three macro areas of the ESG analysis, each of which is divided into a positive and a negative cluster for sentiment analysis purposes. A detailed layer of sub-categories for each macro area defines the relevant topics.

1000 Environment
    1100 Positive
        1110 Climate Impact
        1120 Biodiversity and Environmental Footprint
        1130 Environmental Opportunities
        1140 Waste and Emissions Management
    1200 Negative
        1210 Climate Impact
        1220 Waste and Emissions Management
        1230 Biodiversity and Environmental Footprint
        1240 Environmental Crime
        1250 Greenwashing
2000 Social
    2100 Positive
        2110 Human Capital
        2120 Workplace and Product Safety
        2130 Cybersecurity
        2140 Diversity and Inclusion
        2160 Public Relations
        2170 Community Opportunities
    2200 Negative
        2210 Human Capital
        2220 Workplace and Product Safety
        2230 Cybersecurity
        2240 Discrimination
        2250 Controversial Profile
3000 Governance
    3100 Positive
        3110 Business Ethics and Transparency
        3120 Board Engagement
        3130 Legal Compliance
        3140 Product Stewardship
    3200 Negative
        3210 Business Ethics and Transparency
        3220 Board Engagement
        3230 Legal Compliance
        3240 Product Stewardship
  • Environment sub-categories:

    • Climate Impact: (positive/negative) climate change related behaviors, especially in terms of strategical decisions or corporate policies on the long term, mainly about—or linked to—CO2 emissions.
    • Biodiversity and Environmental Footprint: (positive/negative) engagement towards the preservation of biodiversity and the use of natural resources.
    • Environmental Opportunities: (positive only) innovations adopted by a company in order to protect the environment and fight climate change, as well as new business projects aiming at preserving the environment.
    • Waste & Emissions Management: (positive/negative) management and reduction of waste production and emissions other than CO2.
    • Environmental Crime: (negative only) illicit activities affecting the environment.
    • Greenwashing: (negative only) deceptive ways of using green marketing.
  • Social sub-categories:

    • Human Capital: (positive/negative) social quality of the working environment.
    • Workplace Safety and Product Safety: (positive/negative) refers to the security guaranteed on the workplace and the safety guaranteed for the product or service from the consumer's perspective.
    • Cybersecurity: (positive/negative) data and privacy protection.
    • Diversity and Inclusion: (positive only) inclusiveness and equality initiatives in terms of rights and representativeness.
    • Controversial Profile: (negative only) cases in which a company public image or perception is controversial.
    • Public Relations: (positive/negative) communication strategies.
    • Community Opportunities: (positive only) community support investments.
    • Discrimination: (negative only) events denoting discrimination in terms of rights and representativeness.
  • Governance sub-categories:

    • Business Ethics and Transparency: (positive/negative) the quality and truthfulness levels of the information delivered to the public and the stakeholders, as well as the company compliance with basic business ethical principles, in terms of financial actions, reliability and competitiveness.
    • Board Engagement: (positive/negative) overall engagement of board members, in terms of social and business activity.
    • Legal Compliance: (positive/negative) compliance with the relevant legislation.
    • Product Stewardship: (positive/negative) engagement towards product quality.

Along with the third level categories, the corresponding second and first level categories are always found in the categorization output. This allows you to see how the scores of the leaf categories are transmitted to the higher level categories in order to compute the overall sentiment indicators present in the ESG_SENTIMENT record of the extraction output (see below).
Only the third level categories, however, are directly triggered by the input text, so they are the only ones for which the positions to be highlighted in the text are provided.

Extraction

Introduction

The information extraction activity of the detector finds and returns records of extracted information. Each record contains data fields and its structure—the possible fields—is called template.
A template can be compared to a table and the template fields to the columns of the table, as shown in the following figure.

ENTITY template

The detector extracts references found in the input text to entities performing ESG-related actions or making ESG-related statements.
Each extraction is a record of the ENTITY template with one or more occurrences of the following fields:

Field Description
entity Entity name
CO2_emission_cut CO2 emissions reduction (percentage)
CO2_emission_increase CO2 emissions increase (percentage)
certification_obtained An ESG certification
date Date of CO2 or pollution reduction/increase
inference Anaphora of the entity name
pollution_increased Emissions increase, other than CO2 (percentage)
pollution_decreased Emissions reduction, other than CO2 (percentage)
waste_increased Waste production increase (percentage)
waste_decreased Waste production decrease (percentage)
sanction Amount of money due by an entity because of code or law infringements

ESG_SENTIMENT template

The detector also extracts summary ESG performance indicators for the whole document. They are records of the ESG_SENTIMENT template with these fields:

Field Description
overall_score Overall ESG sentiment score (no range)
overall_sentiment Overall sentiment polarity, either positive or negative based on the sign of overall_score
environment_performance_score Environment score
environment_sentiment Environment sentiment polarity, either positive or negative based on the value and sign of environment_performance_score
social_performance_score Social sentiment score (no range)
social_sentiment Social sentiment polarity, either positive or negative based on the value and sign of social_performance_score
governance_performance_score Governance sentiment score (no range)
governance_sentiment Governance sentiment polarity, either positive or negative based on the value and sign of governance_performance_score
sum_environment_rules Diagnostic information
sum_social_rules Diagnostic information
sum_governance_rules Diagnostic information

Useful resources