Earticle

초록

영어

The purpose of this study is 1) to examine the types of tweets including #patient31 and evaluative language use of the tweets within the framework of Systemic Functional Linguistics, Appraisal Framework, and Critical Discourse Analysis; and 2) to show how the shared evaluation for patient31 represents her negatively and even reinforces the fixed image of ‘a reckless, irresponsible super spreader of virus.’ 101 tweets including the hashtag ‘#patient31’ were scraped randomly. The findings revealed that the hashtag and its linguistic use served both ideational function and interpersonal function. Communicating their evaluation for patient31, users shared their opinions, emotions, and lastly, built solidarity, and even ambient affiliation. The mutual consent to the evaluation or meaning-making process is realized in the phrase ‘don’t be patient31.’ However, there was a voice warning that this kind of meaning-making became cyberbullying toward an infected person. This study found that it is worth analyzing the language of SNS to show its multifunction rather than just its informational role.

목차

Abstract
1. Introduction
2. Twitter and Hashtag
3. Systemic Functional Linguistics and Appraisal Framework
3.1. Critical Discourse Analysis and Systemic Functional Linguistics
3.2. Appraisal Framework
4. Methods
4.1. Background and Data
4.2. Analysis
5. Discussion and Conclusion
References

키워드

저자

• Yeseul Choi [ Daedeok Highschool/Teacher ] First author
• Sujung Min [ Kongju National University/Professor ] Corresponding author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  언어과학 [Journal of Language Sciences]

• 간기

  계간

• pISSN

  1225-2522

• 수록기간

  1994~2025

• 등재여부

  KCI 등재

• 십진분류

  KDC 705 DDC 405