A Novel Methodology for Generating Demographically Representative Fictional Identities
Keywords:
Abstract
I n an increasingly digitized and data-driven world the capacity to generate synthetic data that can simulate real-world situations is of immense importance It has become particularly relevant in various fields such as data analysis software testing social science simulations and even creative writing These applications often require large sets of data that imitate real- life contexts while ensuring that they are entirely fictional and do not infringe upon individual privacy 9 This paper introduces a novel methodology for creating demographically representative fictional identities specifically designed to reflect the demographic distribution of the United States Creating synthetic identities that match specific demographic distributions presents several benefits
Downloads
- Article PDF
- TEI XML Kaleidoscope (download in zip)* (Beta by AI)
- Lens* NISO JATS XML (Beta by AI)
- HTML Kaleidoscope* (Beta by AI)
- DBK XML Kaleidoscope (download in zip)* (Beta by AI)
- LaTeX pdf Kaleidoscope* (Beta by AI)
- EPUB Kaleidoscope* (Beta by AI)
- MD Kaleidoscope* (Beta by AI)
- FO Kaleidoscope* (Beta by AI)
- BIB Kaleidoscope* (Beta by AI)
- LaTeX Kaleidoscope* (Beta by AI)
How to Cite
Published
2023-10-28
Issue
Section
License
Copyright (c) 2023 Authors and Global Journals Private Limited

This work is licensed under a Creative Commons Attribution 4.0 International License.