Earticle

초록

영어

Recently, the amount of newly coined words generated in Korean is vast, and the frequency of use in official language media such as the media, broadcasting, and books as well as everyday spoken language is gradually increasing. As the time spent in the Internet space increases, language for communication is created in various forms or its meaning changes to convey new information or values to members of society. In this study, the SNS corpus containing the rapidly changing use of language was analyzed. After selecting new word candidates by constructing a series of pipelines for extracting noun-type new words from the SNS corpus, characteristics and usage were analyzed. At this time, in the natural language processing pipeline that extracts new words, a pipeline including all the processes of rule-based learning using Mecab, unsupervised learning using Soynlp, and user dictionary addition using a correct morpheme analyzer was constructed to extract meaningful tokens. After completing the step of selecting new word candidates, 255 new words were collected. The proportion of sentences including the new word candidate group in the SNS data was 4.799%. Among them, the proportion of sentences in which words belonging to the top 10 appeared was 12.345%. Looking at the ratio of classifying the top 30 new words according to the word formation method, the word formation method that occupied the highest ratio was compound word-synthetic abbreviations (33.3%). The type/token ratio of sentence data including new words was 0.324. The type/token ratio of SNS data was 0.254. Since the type/token ratio of SNS data is lower, it can be said that ototoxicity is higher than that of sentences containing new words. When looking at the collocation relationship and usage of new words such as the initial constant word 'ㄹㅇ', the borrowed word '-특', and the meaning-expanded word '코인', various forms and syntactic uses could be found, and there were many collocations that reflected the social image at the time of data collection. Judging from this phenomenon, the characteristics of corpus, in which initials, borrowings, meeaning-expandings, and special characters are used among newly coined words, become incomplete when simply relying on a dictionary consisting of words or word lists, so a natural language processing dataset containing more diverse social meanings can be constructed by using usage data.

목차

ABSTRACT
1. 서론
2. 이론적 배경
2.1. 용어 정의
2.2. 형태소 분석기 선정
2.3. OOV 문제를 해결하기 위한 파이프라인 구축
3. 연구 방법
3.1. 연구 대상
3.2. 연구 설계
4. 결과 및 논의
4.1. 상위어 용례 분석
4.2. 단어사전 구축의 문제점
4.3. 형태론적 이형태 분류 문제
4.4. 특수문자 처리 문제점
5. 결론
참고문헌

키워드

저자

• 이도영 [ 충남대학교 학부생 ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  Corpus Linguistics Research

• 간기

  계간

• pISSN

  2465-812X

• 수록기간

  2015~2025

• 십진분류

  KDC 701 DDC 410