The Korean Society for Journalism & Communication Studies (KSJCS)

[ Theory Method ]

Korean Journal of Journalism & Communication Studies - Vol. 62, No. 4, pp.125-158

ISSN: 2586-7369 (Online)

Print publication date 31 Aug 2018

Received 15 Jun 2018 Revised 13 Jul 2018 Accepted 02 Aug 2018

DOI: https://doi.org/10.20879/kjjcs.2018.62.4.004

미세먼지 재해 보도의 프레임 분석 : 구조적 주제모형(Structural Topic Modeling)의 적용

이준웅^** ; 김성희^***

**서울대학교 언론정보학과 교수, 교신저자 jwrhee@snu.ac.kr
***서울대학교 언론정보학과 박사과정 mynameis.sungheekim@gmail.com

News frames in the coverage of fine-dust disaster : Application of Structural Topic Modeling

June Woong Rhee^** ; Sung-hee Kim^***

**Professor, Seoul National University jwrhee@snu.ac.kr
***Ph. D. Candidate, Seoul National University mynameis.sungheekim@gmail.com

초록

이 연구는 우리나라 중앙일간지의 미세먼지 보도의 특징을 검토하기 위해, 전통적인 내용분석 방법을 사용해서 분석유목을 정해 놓고 뉴스 프레임을 확인한 결과를 ‘자료기반적’ 방법으로 구조적 주제모형(STM)을 적용해서 뉴스 프레임을 추출한 결과와 비교했다. 먼저, 2013년 1월부터 2017년 5월까지 3,636개의 미세먼지 관련 보도를 대상으로 구조적 주제모형을 적용한 결과 30개의 잠재적 주제를 찾아냈는데, 여기에 군집분석을 적용해서 5개의 주제적 뉴스 프레임을 구성했다. 덧붙여 전체 기사 중 300개 미세먼지 기사를 표집해서, 이로부터 재해관련 선행연구에서 검토한 주제적 요소를 분석유목을 삼아 연구자가 직접 코딩하는 방식으로 프레임을 규정했다. 두 가지 프레임 분석 결과를 비교해서 ‘자료기반적’ 뉴스 프레임 추출 방법의 가능성을 검토했다. 최종적으로 구조적 주제모형을 적용한 뉴스 프레임을 이용해서 미세먼지 보도에 나타나는 주제적 프레임의 분포가 언론사에 따라, 그리고 시기별로 다르게 나타났음을 확인했다. 연구결과에 기초해서 한국 언론의 미세먼지 재해 보도가 보이는 ‘파편화된 보도’ 현상의 함의를 논의했다.

Abstract

Employing two different methods of finding news frames in the coverage of fine-dust disaster, this study explored the ways in which major newspapers reported fine-dust from 2013 to 2017 in South Korea. The traditional way of identifying news frames is to conduct content analysis with a pre-defined set of frames considered to be themes and other related textual features. In addition to employing this traditional content analytic method, this study also undertook an algorithmic approach to finding underlying themes of a news corpus using the technique of structural topic modeling (STM), which made it possible to make a comparison between the results from the two approaches. Five different sets of underlying topics, defined as news frames in this study, were identified from a corpus comprising of 3,636 fine-dust related articles. Four different thematic news frames were found using a manual coding of news frames on 300 cases systematically sampled from the 3,636 articles. Similarities and dissimilarities between two sets of frames were examined and accounted for by methodological factors concerning data-driven vs. concept-driven content analysis. The findings of frame distributions across different news media and time periods were discussed in terms of media factors as well as issue characteristics of the fine-dust disaster.

Keywords:

fine-dust, disaster, risk perception, news frames, structural topic modeling (STM)

키워드:

미세먼지, 재난, 위험 인식, 뉴스 프레임, 구조적 주제모형, 토픽모델링

Acknowledgments

이 연구는 서울대학교 언론정보연구소의 연구지원을 일부 받았음을 밝힙니다. 자료분석 초기단계에서 연구방법론과 관련해서 도움을 주신 백영민 교수에게 감사를 표합니다.

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