Employee Sentiment Analysis Using Regression and NLP
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Solution Overview
Problem
Organizations face challenges in retaining employees due to inadequate methods for identifying employee satisfaction or dissatisfaction, as they primarily rely on performance data rather than behavioral and sentiment analysis, leading to high attrition rates and recruitment costs.
Innovation Solution
A method and system that extracts structured and unstructured data to create employee profiles, using regression models and Natural Language Processing (NLP) to generate a sentiment matrix indicating satisfaction or dissatisfaction levels, enabling proactive corrective measures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If organizations rely on performance data to analyze employee satisfaction, then the analysis process is simple, but the measurement precision of employee sentiments is insufficient
Solution Approach 1:
The patent combines structured data (performance metrics, attendance records) with unstructured data (email communications, survey responses, social media posts) to create a comprehensive employee sentiment analysis system. This merging of diverse data types enables precise sentiment identification while maintaining system manageability through integrated processing workflows.
Solution Approach 2:
The patent introduces natural language processing (NLP) techniques as an intermediary to bridge the gap between unstructured textual data and actionable sentiment insights. The NLP component processes communications and extracts sentiment indicators, enabling accurate measurement without requiring direct manual analysis of each data point.
2Measurement precision
If organizations implement comprehensive sentiment analysis using both structured and unstructured data, then the measurement precision improves, but the device complexity increases
Solution Approach 1:
The patent segments the sentiment analysis system into distinct functional modules: structured data extraction from HR systems, unstructured data collection from communications, NLP processing components, and sentiment synthesis algorithms. This segmentation reduces overall system complexity by making each component independently manageable while maintaining precise sentiment identification through their integrated operation.
3Productivity
If organizations wait until employees plan to leave to provide retention benefits, then the financial cost is reduced, but the productivity loss increases due to high attrition rates
Solution Approach 1:
The patent implements preliminary sentiment analysis to identify employees showing signs of dissatisfaction before they actually leave. By analyzing patterns in communications, performance data, and engagement metrics, the system enables organizations to take preventive retention actions early, avoiding the costs of recruitment and training while maintaining productivity.
Solution Approach 2:
The patent establishes continuous feedback loops where sentiment analysis results are fed back to HR and management teams, enabling real-time intervention strategies. This feedback mechanism allows organizations to adjust retention efforts dynamically based on actual employee sentiment trends, optimizing both productivity and resource allocation.
Data Source
AI summary
A method and system for determining sentiment of an employee towards an organization comprises extracting structured and unstructured data from one or more structured data sources comprising structured datapoints and one or more unstructured data sources comprising unstructured datapoints. The method comprises building regression model on the plurality of structured datapoints to determine a relationship of structured datapoints amongst the structured datapoints, creating a first profile of the employee based on said relationship, creating a second profile of the employee by selecting one or more words from each unstructured datapoints by using a prestored vocabulary, assigning one or more scores, corresponding to said words, in context of corresponding each of the unstructured datapoints. Method comprises generating a matrix based on the first profile and the second profile indicating sentiments of employee towards organization.