• International journal of advanced smart convergence
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• 제12권1호
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• pp.82-91
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• 2023

In 2020 when the COVID-19 pandemic began in full-scale, the WHO Director-General warned of the dangers of an infodemic. The infodemic is a phenomenon in which false information spreads rapidly like an epidemic and causes chaos, and it was noted that the COVID-19 pandemic is not just limited to health problems, but also linked to a variety of issues such as human rights, economic inequality, various discrimination, hate speech, fake news, global governance etc. In the field of education, it is necessary to think about how to connect this global situation with school classes. Accordingly, this study suggested the direction for global citizenship education by analyzing how the infodemic spreads on Korean social media with the case of the recent global COVID-19 pandemic. According to the research results, the rate of negative emotions was higher than positive ones in the emotions that generate infodemic, while anxiety and anger were focused among negative emotions. In addition, the infodemic tended to spread widely with the feelings of anger rather than anxiety, and the feelings of anger led to advocating aggressive policies against certain country and regions. Therefore, global citizenship education is required to focus on a sense of duty and responsibility as a citizen, not on the level of national identity based on an exclusive sense of belonging. Furthermore, global citizenship education needs to lead to presenting a blueprint for education in a way that can enhance the awareness of the global community for joint response to global challenges and realize common prosperity based on sustainability and justice.

• Journal of Information Science Theory and Practice
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• 제10권1호
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• pp.59-72
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• 2022

This text discusses elements and characteristics of contemporary informational reality, that is, the ways of producing, circulating, organizing, using, and appropriating information in the current context. Initially, seven terms and concepts used to describe this reality are discussed: fake news, false testimonials, hate speech, scientific negationism, disinformation, post-truth, and infodemic. Next, an attempt is made to present a framework for such phenomena as an object of study in information science. Therefore, this scenario is characterized based on the three main models of information science study: physical, cognitive, and social. The contribution of each of them to the study of contemporary informational reality is analyzed, identifying aspects such as the bubble effect, clickbaits, confirmation bias, cults of amateurism, and post-truth culture. Finally, it presents the discussion of a possible veritistic turn in the field, in order to think about elements not covered so far by information science in its task and challenge of producing adequate understanding and diagnoses of current phenomena. In conclusion, it is argued that only accurate and comprehensive diagnoses of such phenomena will allow information science to develop services and systems capable of combating their harmful effects.

• Journal of Preventive Medicine and Public Health
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• 제53권5호
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• pp.311-312
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• 2020

• Asia pacific journal of information systems
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• 제32권4호
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• pp.945-963
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• 2022

With the widespread use of social media, online social platforms like Twitter have become a place of rapid dissemination of information-both accurate and inaccurate. After the COVID-19 outbreak, the overabundance of fake information and rumours on online social platforms about the COVID-19 pandemic has spread over society as quickly as the virus itself. As a result, fake news poses a significant threat to effective virus response by negatively affecting people's willingness to follow the proper public health guidelines and protocols, which makes it important to identify fake information from online platforms for the public interest. In this research, we introduce an approach to detect fake news using deep learning techniques, which outperform traditional machine learning techniques with a 93.1% accuracy. We then investigate the content differences between real and fake news by applying topic modeling and linguistic analysis. Our results show that topics on Politics and Government services are most common in fake news. In addition, we found that fake news has lower analytic and authenticity scores than real news. With the findings, we discuss important academic and practical implications of the study.

• Journal of Information Technology Applications and Management
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• 제28권5호
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• pp.41-50
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• 2021

As COVID-19 spread widely, and rapidly, the number of misinformation is also increasing, which WHO has referred to this phenomenon as "Infodemic". The purpose of this research is to develop detection and rectification of COVID-19 misinformation based on Open-domain QA system and text similarity. 9 testing conditions were used in this model. For open-domain QA system, 6 conditions were applied using three different types of dataset types, scientific, social media, and news, both datasets, and two different methods of choosing the answer, choosing the top answer generated from the QA system and voting from the top three answers generated from QA system. The other 3 conditions were the Closed-Domain QA system with different dataset types. The best results from the testing model were 76% using all datasets with voting from the top 3 answers outperforming by 16% from the closed-domain model.

• 문화기술의 융합
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• 제7권3호
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• pp.163-171
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• 2021

이 연구는 코로나19가 야기한 인포데믹 상황에서 유튜브상에서 확산된 코로나19 백신 관련 영상의 주요 특성과 이용자 반응의 차이를 알아보고자 하였다. 코로나19 백신 관련 영상 579개에 대한 내용분석 결과, 허위정보는 모두 개인 채널이 저자인 것으로 나타났으며, 기관 및 단체, 언론사, 정부 채널에서는 사실 중심 보도와 더불어 허위정보에 대한 보도도 한 축을 이룬 것으로 나타났다. 진보 성향의 채널은 백신 접종을 찬성하는 긍정적 정서의 비율이 높았고, 보수 성향의 채널은 백신 접종에 반대하는 부정적 정서의 비율이 높았다. 백신 접종이 시작된 이후에 정부 채널의 영상이 증가했고, 긍정적 정서의 영상이 증가한 것으로 나타났다. 좋아요 수에 영향을 미치는 영상의 특성 요인을 회귀분석을 통해 알아본 결과, 개인 전문가 영상, 진보 성향 채널의 영상이 좋아요를 더 많이 받은 것으로 나타났다. 연구 결과를 종합하여 소셜미디어를 활용한 코로나19 백신 관련 정부 정책 홍보 방안에 대해 제시하였다.

• Asian Journal for Public Opinion Research
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• 제12권1호
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• pp.53-74
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• 2024

The proliferation of health misinformation gained momentum amidst the outbreak of the novel coronavirus disease 2019 (COVID-19). People stuck in their homes, without work pressure, regardless of health concerns towards personal, family, or peer groups, consistently demanded information. People became engaged with misinformation while attempting to find health information content. This study used the content analysis method and analyzed 1,154 misinformation stories from four prominent signatories of the International Fact-Checking Network during the pandemic. The study finds the five main categories of misinformation related to the COVID-19 pandemic. These are 1) the severity of the virus, 2) cure, prevention, and treatment, 3) myths and rumors about vaccines, 4) health authorities' guidelines, and 5) personal and social impacts. Various sub-categories supported the content characteristics of these categories. The study also analyzed the emotional valence of health misinformation. It was found that misinformation containing negative sentiments got higher engagement during the pandemic. Positive and neutral sentiment misinformation has less reach. Surprise, fear, and anger/aggressive emotions highly affected people during the pandemic; in general, people and social media users warning people to safeguard themselves from COVID-19 and creating a confusing state were found as the primary motivation behind the propagation of misinformation. The present study offers valuable perspectives on the mechanisms underlying the spread of health-related misinformation amidst the COVID-19 outbreak. It highlights the significance of discerning the accuracy of information and the feelings it conveys in minimizing the adverse effects on the well-being of public health.

• 한국컴퓨터정보학회논문지
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• 제26권8호
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• pp.91-101
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• 2021

본 논문은 COVID-19로 인해 세계적인 팬데믹(Pandamic)을 경험하게 되면서 보건 분야, 정책 분야 등에 있어 포스트 코로나(Post-Corona)를 준비하기 위한 시사점을 도출하고자 한다. 국내 감염병 방역체계가 가동되었던 SARS-CoV, MERS-CoV, SARS-CoV-2(COVID-19)의 3개 감염병에 대해 발병 1년간의 시기적인 분석을 통해 언론사 뉴스 및 트렌드를 분석해보자는 것이다. 이를 위해 한국언론진흥재단 '빅카인즈' 뉴스 분석 프로그램을 활용하여 각 감염병이 국내에 영향이 미치던 시기를 기준점으로 1년간의 뉴스 기사 건수를 수치화하고 주요 트렌드를 워드클라우드로 구현하여 분석하였다. 분석 결과, 감염병과 관련한 기사 건수는 세계보건기구(WHO)의 경고 선언 및 (의심)확진자 발생 시점에 정점을 기록하였다. 키워드와 워드클라우드 분석에 따르면 감염병에 대한 '발병지 및 주요 유행지역', '방역당국', '질병정보 및 확진자 정보' 등이 주요한 공통점으로 나타났으며, 3개 감염병에서 차이점을 도출하였다. 아울러, 불확실 정보에 대하여 워드클라우드 분석을 수행함으로써 인포데믹 현황을 파악하였다. 본 연구결과는 앞서 경험하고 있는 감염병을 통해서 새로운 질병이 대유행할 시 선행되어야 하는 보건당국, 언론의 역할 및 재정비되어야 할 영역을 도출할 수 있었다는 점에서 의의를 갖는다.