메뉴 건너뛰기
.. 내서재 .. 알림
소속 기관/학교 인증
인증하면 논문, 학술자료 등을  무료로 열람할 수 있어요.
한국대학교, 누리자동차, 시립도서관 등 나의 기관을 확인해보세요
(국내 대학 90% 이상 구독 중)
로그인 회원가입 고객센터 ENG
주제분류

추천
검색
질문

논문 기본 정보

자료유형
학술저널
저자정보
Chae-yun Lim (Yonsei University) Misa Park (Yonsei University) Young Min Baek (Yonsei University)
저널정보
한국언론학회 Asian Communication Research Asian Communication Research Vol.16 No.1
발행연도
2019.5
수록면
13 - 71 (59page)
DOI
10.20879/acr.2019.16.1.13

이용수

표지
📌
연구주제
📖
연구배경
🔬
연구방법
🏆
연구결과
AI에게 요청하기
추천
검색
질문

초록· 키워드

오류제보하기
This study presents an automated content analysis of 2,379 abstracts of research articles published in four major journals from 1997 to 2017. A total of 45 topics were extracted using the structural topic model (STM), a statistical text analytic method that allows us to infer latent topics from abstracts and to conduct statistical significance tests regarding the relationships between topic prevalence and abstract features. We found that while some topics (e.g., public health or online social movement) demonstrate increasing trends, others (e.g., third-person effect and communication strategies) reveal decreasing trends; authors in non-US-based institutions are more likely than those affiliated with US-based institutions to focus on the societal consequences of media (e.g., agenda-setting effect or public deliberation). Additionally, interesting relationships were found between topic prevalence and the number of article authors (e.g., popular topics among multi-author papers are lab-based experiments or large-scale campaign studies). Finally, topic-journal associations were identified.

목차

Abstract
Introduction
Methods
Results
Discussion
References

참고문헌 (31)

참고문헌 신청

함께 읽어보면 좋을 논문

논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!

이 논문의 저자 정보

최근 본 자료

전체보기

댓글(0)

0

UCI(KEPA) : I410-ECN-0101-2019-070-000716071