Week 12 Final / Graduation Project:

Measuring Organizational Practices from Employee Reviews

This project was completed in the final week of the Data Science Bootcamp at Spiced Academy in Berlin.

This is a dictionary that measures organizational practices from employee reviews. The project has the following work-flow.

• Collect / prep data / corpus --- Cheers to Matthew Chatham
• Explore data & obtain seed words
  • Topic modeling
  • Joint Maximum Likelihood Estimation for High-Dimensional Item Factor Analysis
  • deep artificial neural network model: importance-weighted autoencoder for exploratory IFA --- Cheers to Christopher J. Urban
• Build the dictionary with word2vec --- Cheers to Kai Li, Feng Mai, Rui Shen, Xinyan Yan
• Validate the dictionary
  • Check for the pattern of correlations across train / test sets
    • Dictionary (saliency) scores & employee ratings
    • Repeat the step above with a different corpus
    • Dictionary (saliency) scores & topic sentiments (estimated with joint sentiment topic models) & regular sentiment scores
  • Check the associations between dictionary (saliency) scores & dimensions obtained with autoencoders
• Visualizations

Use case

The measurement instrument is good for quantifying the saliency of the following in employee reviews.

• the conflict between the interests of employees vs. organization
• the conflict between employees’ independence to organize their own work vs. need for control & centralization
• the conflict between stability & change

There is simply no good or bad company culture! By utilizing this measurement instrument companies can see where they are in comparison to

industry averages

as well as

company averages

and perhaps try to aim for a culture that supports their business strategies and goals.

Disclaimer

This is an ongoing project, which may end up being a product. At this stage I'm sharing the dictionary as a .dic file in LIWC format.

TO-DO

• Explore the associations with some ground truth
  • revenues / revenue %s for employee well-being
  • hiring & firing %s
  • ranking in global innovation index
  • etc.
• The current version is based on "employees talking about their companies" type of text data
  • collect & append "companies talking about themselves" type of text data for a more accurate picture of organizational culture

Presentation slides are available at https://1drv.ms/p/s!AuQR1pEfkazyliMRvAgVAqcpZ9Ze?e=6k6kS7