All About the Name: Assigning Demographically Appropriate Names to Data-Driven Entities

Abstract

We develop a method for assigning demographically appropriate names to data-driven entities, such as personas, chatbots, and virtual agents. The value of this method is removing the time-consuming human effort in this task. To demonstrate our method, we collect four million user profiles with gender, age, and country information from an international online social network. From this dataset, we obtain 1, 031, 667 unique names covering 3, 088 demographic group combinations that our method considers as gender, age, and nationality appropriate. A manual evaluation by raters from 34 countries shows a demographic appropriateness score of 85.6%. The demographically appropriate names can be utilized for data-driven personas, virtual agents, chatbots, and other humanized entities.