Voice Share Calculation for ESG Controversy Influence
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Solution Overview
Problem
There is a lack of a quantitative metric to assess a company's Environmental, Social, and Governance (ESG) impact, particularly in determining the influence of organizations on ESG controversies, which hinders investors' ability to evaluate risks and future financial performance.
Innovation Solution
A method and system to calculate an organization's 'voice share' by identifying relevant keywords, determining external and internal voice scores based on information sources, and combining these to assess the organization's influence on ESG controversies relative to peers within the same industry sector.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional qualitative assessment methods are used to evaluate company ESG impact, then the assessment process is simple and easy to implement, but the measurement precision and objectivity are insufficient
Solution Approach 1:
The patent segments the ESG impact assessment into multiple dimensions: voice share calculation (internal vs. external sources), sentiment analysis (positive vs. negative vs. neutral), and controversy classification. This segmentation allows for precise measurement of each component while maintaining systematic organization, resolving the contradiction between measurement precision and system complexity.
Solution Approach 2:
The patent introduces quantifiable parameters including voice share percentages, sentiment scores, controversy intensity metrics, and influence weights. By transforming qualitative ESG concepts into measurable parameters, the system achieves high measurement precision while the automated calculation processes manage the complexity through standardization.
2Measurement precision
If comprehensive data from multiple information sources is collected to assess organizational influence, then the measurement accuracy improves, but the data processing complexity and time consumption increase
Solution Approach 1:
The patent performs preliminary actions by pre-identifying relevant information sources, pre-defining controversy topics, and pre-establishing sentiment analysis frameworks. This preparation work is done before the actual assessment, allowing the system to quickly process data during execution without re-evaluating source relevance or analysis methodologies, thus reducing processing time while maintaining comprehensive data collection.
Solution Approach 2:
The patent replaces manual data collection and analysis mechanisms with automated computational systems. Machine learning algorithms automatically scrape, classify, and analyze data from multiple sources, substituting time-consuming manual processes with efficient automated systems that maintain high measurement accuracy while significantly reducing processing time.
3Adaptability or versatility
If both internal and external information sources are analyzed to calculate voice scores, then the assessment comprehensiveness improves, but the system complexity increases
Solution Approach 1:
The patent applies local quality by treating internal and external information sources differently with distinct analysis methodologies. Internal sources (company reports, press releases) receive different weighting and sentiment analysis treatment compared to external sources (media coverage, social media, analyst reports). This differentiated approach enhances comprehensiveness while managing complexity through targeted processing rules for each source type.
Solution Approach 2:
The patent introduces an intermediary layer that standardizes and normalizes data from diverse internal and external sources before analysis. This intermediary processing layer harmonizes different data formats, credibility weights, and sentiment scales, enabling comprehensive multi-source analysis while managing complexity through standardization protocols.
Data Source
AI summary
A method of determining controversy voice share is provided. The method comprises identifying keywords related to a controversy topic and identifying information sources relevant to the controversy topic based on occurrences of the keywords within each source. An external voice score is calculated for an organization regarding the controversy topic, wherein the external voice score is calculated based on information sources that are external to the organization. An internal voice score is calculated for the organization regarding the controversy topic, wherein the internal voice score is calculated based on information sources internal to the organization. An overall voice share of the organization is then calculated from the external voice score and internal voice score. The overall voice share of the organization represents a proportion of influence the organization contributes to public commentary on the controversy topic relative to other organizations within a same industry sector.