AI Agents

Detecting patterns of discrimination in the workplace using AI

38 nodes 224 130 Automatic trigger
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Workflow Description

An advanced automation system that analyzes social media posts and text data to detect workplace discrimination patterns using artificial intelligence and natural language processing models.

How it works

  1. 1.Activate the workflow manually and collect text data from multiple sources
  2. 2.Process texts through advanced LLM chains and analyze content using OpenAI models
  3. 3.Extract suspicious indicators and patterns, categorizing them by severity levels
  4. 4.Generate visual reports and charts that illustrate the findings
  5. 5.Consolidate data and merge results from parallel processing operations

Use cases

  • Monitor social media platforms to identify discriminatory language targeting specific groups
  • Analyze internal complaint logs and messages to detect systematic bias patterns
  • Create periodic HR reports on potential discrimination indicators across the organization

Requirements

  • Valid OpenAI API key for running advanced language models
  • Secure connection to Twitter/X accounts or alternative text data sources
  • Basic understanding of LLM chain configuration and custom parameters

Service Value

Ideal as a smart automation service combining integrations and AI to produce ready-to-use results.

Apps Used

OpenAI Twitter/X Quick Chart LLM Chain

Details

Trigger Automatic trigger
Nodes 38
Apps 4
Views 224
Downloads 130

How to Use

  1. 1.Click "Download Template"
  2. 2.Open your n8n dashboard
  3. 3.Go to Workflows > Import from File
  4. 4.Select downloaded file and configure credentials

Nodes Used (38)

/

When clicking ‘Test workflow’

Manual Trigger

#1

OpenAI Chat Model1

OpenAI

#2

OpenAI Chat Model2

OpenAI

#3

Merge

Merge

#4

OpenAI Chat Model

OpenAI

#5

SET company_name

Set

#6

Define dictionary of demographic keys

Set

#7

ScrapingBee Search Glassdoor

HTTP Request

#8

Extract company url path

HTML Page

#9

ScrapingBee GET company page contents

HTTP Request

#10

Extract reviews page url path

HTML Page

#11

ScrapingBee GET Glassdoor Reviews Content

HTTP Request

#12

Extract Overall Review Summary

HTML Page

#13

Extract Demographics Module

HTML Page

#14

Extract overall ratings and distribution percentages

Information Extractor

#15

Extract demographic distributions

Information Extractor

#16

Define contributions to variance

Set

#17

Set variance and std_dev

Set

#18

Calculate P-Scores

Code

#19

Sort Effect Sizes

Set

#20

Calculate Z-Scores and Effect Sizes

Set

#21

Format dataset for scatterplot

Code

#22

Specify additional parameters for scatterplot

Set

#23

Quickchart Scatterplot

HTTP Request

#24

QuickChart Bar Chart

Quick Chart

#25

Sticky Note

Sticky Note

#26

Sticky Note1

Sticky Note

#27

Sticky Note2

Sticky Note

#28

Sticky Note3

Sticky Note

#29

Sticky Note4

Sticky Note

#30

Sticky Note6

Sticky Note

#31

Sticky Note7

Sticky Note

#32

Sticky Note8

Sticky Note

#33

Sticky Note9

Sticky Note

#34

Sticky Note10

Sticky Note

#35

Sticky Note11

Sticky Note

#36

Sticky Note12

Sticky Note

#37

Text Analysis of Bias Data

LLM Chain

#38

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