All about the name: Assigning demographically appropriate names to data-driven entities

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationProceedings of the 54th Annual Hawaii International Conference on System Sciences, HICSS 2021
EditorsTung X. Bui
PublisherIEEE Computer Society
Pages4034-4042
Number of pages9
ISBN (Electronic)9780998133140
Publication statusPublished - 2021
Event54th Annual Hawaii International Conference on System Sciences, HICSS 2021 - Virtual, Online
Duration: 4 Jan 20218 Jan 2021

Publication series

NameProceedings of the Annual Hawaii International Conference on System Sciences
Volume2020-January
ISSN (Print)1530-1605

Conference

Conference54th Annual Hawaii International Conference on System Sciences, HICSS 2021
CityVirtual, Online
Period4/01/218/01/21

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