# Who Is Missing? Characterizing the Participation of Different Demographic Groups in a Korean Nationwide Daily Conversation Corpus

arXiv: https://arxiv.org/abs/2204.09209 · HTML: https://mlsanity.com/paper/2204.09209/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 17 references that are in the map.
- First posted on arXiv 20 Apr 2022.

## Builds on (most cited first, 3 of 3)

- [A Persona-Based Neural Conversation Model](https://mlsanity.com/paper/1603.06155/) (2016)
- [The Ubuntu Dialogue Corpus: A Large Dataset for Research in Unstructured Multi-Turn Dialogue Systems](https://mlsanity.com/paper/1506.08909/) (2015)
- [Neural Responding Machine for Short-Text Conversation](https://mlsanity.com/paper/1503.02364/) (2015)

## Built on by (most cited first, 2 of 2)

- [ChatGPT Rates Natural Language Explanation Quality Like Humans: But on Which Scales?](https://mlsanity.com/paper/2403.17368/) (2024)
- [A Cross-Cultural Comparison of LLM-based Public Opinion Simulation: Evaluating Chinese and U.S. Models on Diverse Societies](https://mlsanity.com/paper/2506.21587/) (2025)

## Abstract (arXiv)

A conversation corpus is essential to build interactive AI applications. However, the demographic information of the participants in such corpora is largely underexplored mainly due to the lack of individual data in many corpora. In this work, we analyze a Korean nationwide daily conversation corpus constructed by the National Institute of Korean Language (NIKL) to characterize the participation of different demographic (age and sex) groups in the corpus.