Who is missing? Characterizing the participation of different demographic groups in a Korean nationwide daily conversation corpus

• Main Authors: KWAK, Haewoon, AN, Jisun, PARK, Kunwoo
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2022
• Subjects: Text categorization; topic recognition; demographic/gender/age identification; Human computer interaction; social media tools; navigation and visualization; New social media applications; interfaces; interaction techniques; Psychological; personality-based and ethnographic studies of social media; Data Storage Systems; Social Media
• Online Access: https://ink.library.smu.edu.sg/sis_research/7499; https://ink.library.smu.edu.sg/context/sis_research/article/8502/viewcontent/19397_Article_Text_23410_1_2_20220531.pdf
• Institution: Singapore Management University

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.