단어 임베딩으로 보는 한국어 젠더의 의미 변화 - 10년 전과 최근의 뉴스 기사를 활용하여 -
Seeing Semantic Changes in Korean Gender through Word Embedding -With Recent News Articles and Articles from the past 10 years
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초록
This paper aims to examine the meaning of gender of various issues in Korean society through word embedding which is a way of expressing distributional semantics, the meaning of language from a large volume of text data. Gender is a form of sociality and refers to the general characteristics that are specified and distinguished by the words male and female. As the technical expression of ‘sociality’ implies, the gender of women and men has changed and the meaning has been related to the characteristics and changes of human groups in society, and it is expressed linguistically. Many sociolinguistic or gender related language studies have investigated the linguistic characteristics of each gender with the utterance of mainly female and male speakers. This is a sociolinguistic variable that explains the difference in the way women and men express their language. On the other hand, the character and meaning of gender can be revealed according to what linguistic expressions are used, when describing woman or man. And the linguistic medium that most reveals various works of human society is newspaper data. Therefore, this article aims to show the change of linguistic aspects which describe and express the events of women and men in news corpus, rather than linguistic variables of women speakers and men speakers.
Abstract
This paper aims to examine the meaning of gender of various issues in Korean society through word embedding which is a way of expressing distributional semantics, the meaning of language from a large volume of text data. Gender is a form of sociality and refers to the general characteristics that are specified and distinguished by the words male and female. As the technical expression of ‘sociality’ implies, the gender of women and men has changed and the meaning has been related to the characteristics and changes of human groups in society, and it is expressed linguistically. Many sociolinguistic or gender related language studies have investigated the linguistic characteristics of each gender with the utterance of mainly female and male speakers. This is a sociolinguistic variable that explains the difference in the way women and men express their language. On the other hand, the character and meaning of gender can be revealed according to what linguistic expressions are used, when describing woman or man. And the linguistic medium that most reveals various works of human society is newspaper data. Therefore, this article aims to show the change of linguistic aspects which describe and express the events of women and men in news corpus, rather than linguistic variables of women speakers and men speakers.
참고문헌 (16)
- Baroni, M, "Frege in space: A program of compositional distributional semantics", LiLT (Linguistic Issues in Language Technology), 9 (2014)
- Bauer L, "Ch.15 Sexist Language and Linguistic Sexism, Language Matters" (2006), Palgrave macmillan
- Bowman, Samuel R, "Modeling natural language semantics in learned representations", Ph.D, pp.2016
- Erez Aiden, "Uncharted: big data as a lens on Human culture", ~ (2013)
- Firth, J. R, "Papers in Linguistics 1934–1951" (1957), Oxford University Press
- Goodfellow, Ian, "Deep learning" (2016), MIT press
- Hamilton, W. L, "Diachronic word embeddings reveal statistical laws of semantic change", Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL2016), pp.1489~1501 (2016)
- Hinton, G. E, "Distributed Representations, Parallel Distributed Processing: Volume1 Foundations" (1986), Volume1 Foundations. MIT press
- Homes, Janet, "An Introduction to sociolinguistics" (2017), Routlegde
- Lakoff, George, "Women, Fire, and Dangerous Things : What Categories Reveal about the Mind" (1987), The University of Chicago Press
- Litosseliti, Lia, "Gender and Language: Theory and Practice" (2006), Hodder Arnold
- Mikolov, T, "Distributed representations of words and phrases and their compositionality", Advances in neural information processing systems (2013)
- Shikha Bordia, "Identifying and Reducing Gender Bias in Word-Level Language Models", Proceedings of the NAACL Student Research Workshop (2019)
- Skeat, Walter William, "An Etymological Dictionary of the English Language" (1882)
- V. Gast, "The Oxford Handbook of Linguistic Typology" (2011), Jae Jung Song)
- Maaten, L. V. D, "Visualizing Data Using t-SNE", Journal of Machine Learning Research, 9, pp.2579~2605 (2008)