치과적 정의에 대한 고찰: 뉴스 댓글 빅데이터 분석을 중심으로
A Critical Review on Dental Justice: Based on Big Data Analysis of News Comments
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Purpose: To seek a new approach to dental justice, this paper identifies public opinions on dental-related social and ethical issues and reviews countermeasures based on them. Methods: Naver news comments, with search term “dental overtreatment” from 2011 (when articles appear as meaningful numbers) to 2022 (present), collected and analyzed by frequency analysis, word network analysis, topic modeling, and BERT-based sentiment analysis. Results: A total of 483 articles and 26, 601 comments (excluding 9,737 comments that do not include text) were collected and analyzed. Comments were biased toward specific articles and events. Word networks and topic modeling presented complaints about medical reality, criticism for the medical community, and medical expenses. Negative emotions related to the issue were increasing. Discussion: Big data analysis of news comments is a tool that allows researchers to check the flow of public opinion related to issues beyond the examination of individual comments, which is often meaningless. The issue of “dental overtreatment” has not been represented much in the media, but the number of related articles and comments is gradually increasing. As confirmed by the categories of the comments, the response to the issue is not focused solely on medical expenses, however, there is a demand for “proper treatment.” Therefore, based on the recent theoretical discussion on the theory of justice, this study presents a different perspective for ap-proaching the issue in dentistry.
Abstract
Purpose: To seek a new approach to dental justice, this paper identifies public opinions on dental-related social and ethical issues and reviews countermeasures based on them. Methods: Naver news comments, with search term “dental overtreatment” from 2011 (when articles appear as meaningful numbers) to 2022 (present), collected and analyzed by frequency analysis, word network analysis, topic modeling, and BERT-based sentiment analysis. Results: A total of 483 articles and 26, 601 comments (excluding 9,737 comments that do not include text) were collected and analyzed. Comments were biased toward specific articles and events. Word networks and topic modeling presented complaints about medical reality, criticism for the medical community, and medical expenses. Negative emotions related to the issue were increasing. Discussion: Big data analysis of news comments is a tool that allows researchers to check the flow of public opinion related to issues beyond the examination of individual comments, which is often meaningless. The issue of “dental overtreatment” has not been represented much in the media, but the number of related articles and comments is gradually increasing. As confirmed by the categories of the comments, the response to the issue is not focused solely on medical expenses, however, there is a demand for “proper treatment.” Therefore, based on the recent theoretical discussion on the theory of justice, this study presents a different perspective for ap-proaching the issue in dentistry.
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