• 정보관리연구
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• 제24권3호
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• pp.31-56
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• 1993

신문(新聞)은 정보원(情報源)으로서 이용도(利用度)가 높다. 각 신문사의 CTS의 도입으로 인하여 신문기사 데이터베이스화(化)가 촉진되어 상용(商用)으로 제공 서비스되는 신문기사의 데이터베이스도 많아졌다. 일본(日本)에서 이용되는 일본과 외국의 주된 신문기사 데이터베이스에 관하여 다음 사항(事項)을 해설하였다. 1) 수록기간, 갱신빈도, 타임 래그, 수록내용, 검색어, 출력 가능한 정보 등 데이터베이스의 특징, 2) 이용시(利用時)의 유의사항, 3) 기업조사, 업계 동향조사 등 조사 목적별의 이용 패턴 등이다. 이러한 데이터베이스는 전자정보의 형태로 이용이 가능하며, 장래에는 사내(社內)의 LAN과 결합하여 이용되리라고 예측된다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2022년도 춘계학술발표대회
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• pp.627-630
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• 2022

Over the past few years, fake news has become one of the most significant problems. Since it is impossible to prevent people from spreading misinformation, people should analyze the news themselves. However, this process takes some time and effort, so the routine part of this analysis should be automated. There are many different approaches to this problem, but they only analyze the text and messages, ignoring the images. The fake news problem should be solved using a complex analysis tool to reach better performance. In this paper, we propose the approach of training an Artificial Intelligence using an unsupervised learning algorithm, combined with online data parsing tools, providing independence from subjective data set. Therefore it will be more difficult to spread fake news since people could quickly check if the news or article is trustworthy.

• 한국전자거래학회지
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• 제17권1호
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• pp.173-187
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• 2012

뉴스 이용 경로가 오프라인 신문에서 온라인 뉴스 매체로 이동하면서, 새로운 여론 형성의 기제로 대두된 댓글에 대한 연구가 많이 이루어져왔다. 댓글에 대한 연구는 주로 댓글의 품질이나 영향력 유무, 여론 형성 기능 등을 중심으로 이루어져왔다. 그런데, 댓글의 여론 형성 기능에 대한 연구 외에, 정치적 민감도가 높은 이슈에 대한 매체별 논조와 개인의 정치성향에 따른 연구는 찾아보기 힘들다. 특히, 이용자의 사회정체성과 정치성향이 그들의 매체선택과 해당 매체에서 접하는 댓글에 대한 인식에 어떠한 영향을 미치는지에 관한 연구는 거의 없었던 것으로 보인다. 이에 본 연구는, 이용자들이 온라인 뉴스 매체와 자신의 정치성향이 유사한 정도에 따라 해당 댓글의 신뢰도, 영향도 등을 다르게 평가하는지에 대해 사회 정체성 이론의 관점에서 살펴보았다. 이를 위해 '개인과 온라인 뉴스 매체 간 정치성향의 유사성'을 독립 변수로 놓고 '댓글에 대한 일반적인 인식'과 '정치성향이 각기 다른 매체의 댓글에 대한 인식'을 종속 변수로 하여 양 변수의 관계를 분석하였다. 동 연구는 댓글 읽기에 초점을 두고 처음으로 정치성향에 따른 매체 이용 패턴과 댓글에 대한 인식을 연구하여 분석했다는 데 학문적 의미를 찾을 수 있을 것이다. 또한, 온라인 뉴스 매체별 댓글 인식의 차이는 댓글 읽기의 중요성과 공론장으로서의 댓글이 유효함을 증명한데 그 의미가 있다.

• 대한간호학회지
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• 제47권6호
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• pp.806-816
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• 2017

Purpose: As comprehensive nursing care service has gradually expanded, it has become necessary to explore the various opinions about it. The purpose of this study is to explore the large amount of text data regarding comprehensive nursing care service extracted from online news and social media by applying a semantic network analysis. Methods: The web pages of the Korean Nurses Association (KNA) News, major daily newspapers, and Twitter were crawled by searching the keyword 'comprehensive nursing care service' using Python. A morphological analysis was performed using KoNLPy. Nodes on a 'comprehensive nursing care service' cluster were selected, and frequency, edge weight, and degree centrality were calculated and visualized with Gephi for the semantic network. Results: A total of 536 news pages and 464 tweets were analyzed. In the KNA News and major daily newspapers, 'nursing workforce' and 'nursing service' were highly rated in frequency, edge weight, and degree centrality. On Twitter, the most frequent nodes were 'National Health Insurance Service' and 'comprehensive nursing care service hospital.' The nodes with the highest edge weight were 'national health insurance,' 'wards without caregiver presence,' and 'caregiving costs.' 'National Health Insurance Service' was highest in degree centrality. Conclusion: This study provides an example of how to use atypical big data for a nursing issue through semantic network analysis to explore diverse perspectives surrounding the nursing community through various media sources. Applying semantic network analysis to online big data to gather information regarding various nursing issues would help to explore opinions for formulating and implementing nursing policies.

• 스마트미디어저널
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• 제7권1호
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• pp.45-51
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• 2018

조류인플루엔자는 전염 속도가 매우 빠르고 양계농장을 중심으로 생산자들과 소비자들에게 심각한 영향을 끼친다. 그중에서도 2016년 말에 전국적으로 발생한 조류인플루엔자는 좁은 공간에 밀집시켜 사육하는 산란계 농장에 큰 피해를 주었다. 이에 따라 달걀과 달걀을 재료로 하는 가공식품의 가격이 급등하였고 언론은 많은 속보성 뉴스기사를 게재하였다. 본 연구는 사회이슈를 반영한 온라인 뉴스기사의 키워드 변화와 달걀가격 변동과의 상관관계를 알아보고자 하였다. 이를 위하여 2016년 11월부터 14주 동안 한국에서 발생한 조류인플루엔자 관련 온라인 뉴스기사 682건과 같은 기간의 달걀가격 변화를 분석하였다. 본 연구의 결과는 사회이슈를 반영하는 뉴스기사의 키워드와 실물가격과의 관계를 이해하는 데 기여할 것으로 기대한다.

• 대한간호학회지
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• 제49권6호
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• pp.736-747
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• 2019

Purpose: This study aimed to explore public opinion on workplace bullying in the nursing field, by analyzing the keywords and topics of online news comments. Methods: This was a text-mining study that collected, processed, and analyzed text data. A total of 89,951 comments on 650 online news articles, reported between January 1, 2013 and July 31, 2018, were collected via web crawling. The collected unstructured text data were preprocessed and keyword analysis and topic modeling were performed using R programming. Results: The 10 most important keywords were "work" (37121.7), "hospital" (25286.0), "patients" (24600.8), "woman" (24015.6), "physician" (20840.6), "trouble" (18539.4), "time" (17896.3), "money" (16379.9), "new nurses" (14056.8), and "salary" (13084.1). The 22,572 preprocessed key words were categorized into four topics: "poor working environment", "culture among women", "unfair oppression", and "society-level solutions". Conclusion: Public interest in workplace bullying among nurses has continued to increase. The public agreed that negative work environment and nursing shortage could cause workplace bullying. They also considered nurse bullying as a problem that should be resolved at a societal level. It is necessary to conduct further research through gender discrimination perspectives on nurse workplace bullying and the social value of nursing work.

• 한국간호교육학회지
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• 제28권4호
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• pp.444-455
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• 2022

Purpose: This study explored the meaning of the social perceptions of nurses in online news articles during the coronavirus disease 2019 (COVID-19) pandemic. Methods: A total of 339 nurse-related articles published in Korean online newspapers from January 1 to December 31, 2020, were extracted by entering various combinations of OR and AND with the four words "Corona," "COVID," "Nursing," and "Nurse" as search keywords using BIGKinds, a news database provided by the Korea Press Foundation. The collected data were analyzed with a keyword network analysis and topic modeling using NetMiner 4. Results: The top keywords extracted from the nurse-related news articles were, in the following order, "metropolitan area," "protective clothing," "government," "task," and "admission." Four topics representing keywords were identified: "encouragement for dedicated nurses," "poor work environment," "front-line nurses working with obligation during the COVID-19 pandemic," and "nurses' efforts to prevent the spread of COVID-19." Conclusion: The media's attention to the dedication of nurses, the shortage of nursing resources, and the need for government support is encouraging in that it forms the public opinion necessary to lead to substantial improvements in treating nurses. The nursing community should actively promote policy proposals to improve treatment toward nurses by utilizing the net function of the media and proactively seek and apply strategies to improve the image of nurses working in various fields.

• 패션비즈니스
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• 제24권4호
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• pp.85-98
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• 2020

The Internet of Things (IoT) shopping environment can provide benefits and risks to consumers, including shopping convenience and invasion of consumer rights, respectively. We experimentally tested whether exposure to information regarding the benefits and risks of IoT shopping would elicit changes to consumer perceptions of the importance of shopping convenience and rights to information, as well as shopping intention among young online shopping consumers. The participants (N=218) were randomly assigned into one of two experimental conditions. The control group was exposed to a news article and a video emphasizing the shopping convenience of the Amazon Dash Button service, while the experimental group was exposed to the same news article and video provided to the control group, along with a news article about the judgment of the Munich court that the Dash Button violates German consumer law. We found an interaction effect of experimental condition and time on changes to the perceived importance of shopping convenience and shopping intention. The changes to the perceived relative importance of shopping convenience to consumer rights to information from pre- to post-manipulation differed significantly between the two experimental groups. The results of this study emphasize the importance of providing information on both the benefits and risks of IoT shopping. This was the first experimental study to examine the possibility of the invasion of consumer rights to information in the IoT shopping environment. This study urges researchers, marketers, and policy makers to focus more on consumer rights to information in the newly coming IoT shopping environment.

• 인터넷정보학회논문지
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• 제17권4호
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• pp.135-143
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• 2016

인터넷은 과학기술 정보를 포함한 다양한 정보의 유통 채널로 널리 활용되고 있다. 이에 본 연구에서는 정보원 공신력에 따라 과학 관련 온라인 뉴스의 설득효과가 어떠한 차이를 보이는가를 대학생들을 대상으로 실험을 통해 살펴보았다. 구체적으로, 온라인 과학기술 뉴스에 등장하는 정보원의 신분(교수, 학생)과 집단구분(내집단, 외집단)을 달리한 실험조건에서 과학기술 메시지를 전달하고 이후 피험자의 과학기술에 대한 유용성 지각과 태도에 미치는 영향을 살펴보았다. 연구결과, 과학기술에 대한 유용성 지각은 정보원 공신력과 내집단 외집단 구분과의 상호작용에 의해 영향을 받는 것으로 나타났다.

• Journal of Information Science Theory and Practice
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• 제7권2호
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• pp.40-53
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• 2019

Although fake news has been present in human history at any time, nowadays, with social media, deceptive information has a stronger effect on society than before. This article answers two research questions, namely (1) Is the dissemination of fake news supported by machines through the automatic construction of filter bubbles, and (2) Are echo chambers of fake news manmade, and if yes, what are the information behavior patterns of those individuals reacting to fake news? We discuss the role of filter bubbles by analyzing social media's ranking and results' presentation algorithms. To understand the roles of individuals in the process of making and cultivating echo chambers, we empirically study the effects of fake news on the information behavior of the audience, while working with a case study, applying quantitative and qualitative content analysis of online comments and replies (on a blog and on Reddit). Indeed, we found hints on filter bubbles; however, they are fed by the users' information behavior and only amplify users' behavioral patterns. Reading fake news and eventually drafting a comment or a reply may be the result of users' selective exposure to information leading to a confirmation bias; i.e. users prefer news (including fake news) fitting their pre-existing opinions. However, it is not possible to explain all information behavior patterns following fake news with the theory of selective exposure, but with a variety of further individual cognitive structures, such as non-argumentative or off-topic behavior, denial, moral outrage, meta-comments, insults, satire, and creation of a new rumor.