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A Gender Identification of Korean Blog Writers through Machine Learning
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- 발행기관
- 한국코퍼스언어학회 바로가기
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- 간행물
- Corpus Linguistics Research 바로가기
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- 통권
- Vol. 7 No. 2 (2022.12)바로가기
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- 페이지
- pp.71-89
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- 저자
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- 언어
- 영어(ENG)
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- URL
- https://www.earticle.net/Article/A426583
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5,400원
원문정보
초록
- 영어
- Choi, J.M.(2023). A gender identification of Korean blog writers through machine learning. Gender identification of texts is a subfield of author analysis; author profiling. This study is an preliminary experiment on an automatic gender detection model for the 1,162 posts of 13 blog owners. As linguistic features, four types of n-gram (word, function word, character, and POS), phoneme frequency, and four lexical sets were chosen, and the support vector machine was adopted as a classifier. The classification accuracy ranged from 54% to 99% depending on the feature type. But the best performing model was produced(obtained) when all the features were inputted combined minus word n-grams. The most salient features distinguishing female from male writers were found to be the first person pronouns( (‘나(I, me)’ and ‘내(+*)’ for females vs. 저(-*)’ and 제(-)’ for males)) and sentence endings(‘다, ‘ᄂ다’ and ‘었다’ for females vs. , ‘습니다’, ‘ᄇ니다’, ‘습니다’, ‘네요’for males). This preliminary study could lead to further research into the gender language variations, and contribute to the development of a stable and robust author profiling system.
목차
ABSTRACT
1. Introduction
2. Related research
3. Method
3.1. Data
3.2. Linguistic features
3.3. Procedures
4. Result
5. Discussion: what are the distinguishing features in gender differentiation?
6. Conclusion
References
키워드
Gender detection SVM Machine learning N-grams Author analysis저자
간행물 정보
발행기관
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- 발행기관명
- 한국코퍼스언어학회 [Korean Association for Corpus Linguistics]
- 설립연도
- 2012
- 분야
- 인문학>언어학
- 소개
- 본 학회는 코퍼스를 연구하거나 코퍼스를 사용하여 언어학 현상을 설명하고자 하는 연구자들로 구성된 학회이며, 코퍼스를 활용하여 다양한 언어현상을 설명하는 것을 설립목적으로 한다.
간행물
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- 간행물명
- Corpus Linguistics Research
- 간기
- 계간
- pISSN
- 2465-812X
- 수록기간
- 2015~2025
- 십진분류
- KDC 701 DDC 410
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