AI-Powered Detection of Workplace Discrimination Patterns from Glassdoor Data

Overview

This workflow leverages AI and web scraping to identify patterns of workplace discrimination by analyzing company reviews from Glassdoor. It automates the collection, processing, and analysis of employee feedback to surface actionable insights.

Key Features

• Automated Data Collection: Uses ScrapingBee to search and extract company review data from Glassdoor.
• AI-Powered Analysis: Employs multiple OpenAI Chat Model nodes to interpret and detect discrimination patterns within unstructured review text.
• Data Structuring: Utilizes set nodes to define demographic keys and organize extracted information for targeted analysis.
• Workflow Orchestration: Merges and manages data flows for efficient processing and result consolidation.

Benefits

• Time Savings: Eliminates manual review of large volumes of employee feedback.
• Actionable Insights: Surfaces hidden patterns of discrimination, supporting HR and compliance efforts.
• Scalable Analysis: Can be adapted to monitor multiple companies or time periods with minimal adjustments.

Use Cases

• HR teams monitoring workplace culture and compliance.
• Consultants conducting diversity and inclusion audits.
• Organizations benchmarking their reputation and employee experience.

Integrations

• OpenAI: For advanced natural language processing.
• ScrapingBee: For reliable web data extraction from Glassdoor.