The Rude Index: Ranking Etiquette & Behaviors With Data Science

The Rude Index is our proprietary machine-learning score. We use it to identify which behaviors are commonly perceived as negative.

Rude Index: how we rank good manners and etiquette with data science

Why apply data science to etiquette?

Etiquette and good manners are often subjective.

A few behaviors are universally good or bad. However, many other behaviors are perceived differently by people. Our perception of good and bad manners depends on a wide set of factors:

  • Personal inclinations.
  • Family norms.
  • Cultural norms.
  • Religion.
  • Geography. Such as country, region, or city.
  • Demographics and personal attributes. Such as age, gender, education, income, or political views.
  • Occasion or context.

The purpose of the Rude Index is to remove subjectivity. The Rude Index aims to identify the behaviors that are objectively disrespectful or widely seen as negative.

How is the Rude Index calculated?

The Rude Index is based on data from multiple sources.

  • Surveys.
  • Expert opinions.
  • Sentiment analysis of online reviews, articles, and other text.

Our algorithms scan such data to identify behaviors and the sentiment and patterns associated with them.

How to use the Rude Index

The Rude Index ranks behaviors by their risk of being perceived negatively. 

  • High scores (8-10) mean that the behavior is widely seen as negative, and it even has the potential to trigger a conflict with others.
  • Medium scores (4-7) mean that the behavior is often seen as negative, and it risks making you look rude, inelegant, or unsophisticated.
  • Low scores (2-3) mean that the behavior can be seen as slightly negative under some circumstances.