Spot Workplace Discrimination Patterns with AI analyzes employee reviews from Glassdoor to identify disparities in workplace experiences among different demographic groups. By leveraging AI and data visualization, it calculates key metrics such as average ratings, z-scores, and effect sizes, highlighting significant gaps in employee satisfaction. This workflow empowers organizations to address inequities and foster a more inclusive workplace environment.
This workflow is designed for:
- HR Professionals: To analyze workplace discrimination patterns based on employee demographics.
- Data Analysts: To extract and interpret data from Glassdoor reviews to identify biases.
- Diversity and Inclusion Officers: To monitor workplace equity and assess the effectiveness of diversity initiatives.
- Company Executives: To gain insights into employee experiences and make informed decisions to improve workplace culture.
This workflow addresses the issue of workplace discrimination by analyzing employee reviews from Glassdoor. It identifies disparities in ratings across various demographic groups, providing insights into potential biases and areas for improvement. By quantifying employee experiences, organizations can take actionable steps to foster a more inclusive environment.
Users can customize this workflow by:
- Changing the Company Name: Modify the company_name
variable to analyze different organizations.
- Adjusting Demographic Keys: Edit the demographic keys in the Define dictionary of demographic keys
step to fit specific needs or add new categories.
- Modifying ScrapingBee Credentials: Update the credentials in the ScrapingBee Search
and ScrapingBee GET
nodes for data access.
- Fine-tuning AI Parameters: Adjust the AI model parameters in the OpenAI nodes to refine data extraction and analysis results.
- Altering Visualization Options: Customize the chart options in the Specify additional parameters for scatterplot
step to change the appearance of the generated visualizations.