• Journal of Information Science Theory and Practice
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• 제11권1호
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• pp.1-13
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• 2023

This study determines how social media users (SMUs) verify the information they come across on the Internet. It determines SMUs' perception of online fact-checking services in terms of their ease of use, usefulness, and trust. By conducting a focus group discussion and key informant interviews, themes were derived in determining fact-checking practices while a survey was further conducted to determine such perceived ease of use, usefulness, and trust in fact-checking services. The thematic analysis revealed major information verification practices, such as cross-checking and verifying with other sources, inspecting comments and reactions, and confirming from personal and social networks. The results showed that SMUs considered fact-checking services easy to use. However, a concern was raised about their usefulness stemming from the delayed action in addressing the information issues that need to be verified. As to perceived trust, it was found that SMUs have reservations about fact-checking services. Finally, it is believed that fact-checking services are expected to be credible and need to be promoted to mitigate any form of fake news, particularly on social media platforms.

• Journal of Information Science Theory and Practice
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• 제8권3호
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• pp.77-90
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• 2020

This study analyzes N=181 social media rumors from Bangladesh to find out the most popular themes, sources, and aims. The result shows that social media rumors have seven popular themes: political, health & education, crime & human rights, religious, religiopolitical, entertainment, and other. Also, online media and mainstream media are the two main sources of social media rumors, along with three tentative aims: positive, negative, and unknown. A few major findings of this research are: Political rumors dominate social media, but its percentage is decreasing, while religion-related rumors are increasing; most of the social media rumors are negative and emerge from online media, and social media itself is the dominant online source of social media rumors; and, most of the health-related rumors are negative and surge during a crisis period, such as the COVID-19 pandemic. This paper identifies some of its limitations with the data collection period, data source, and data analysis. Providing a few research directions, this study also elucidates the contributions of its results in academia and policymaking.

• Journal of Information Processing Systems
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• 제15권5호
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• pp.1029-1035
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• 2019

In recent years, artificial intelligence (AI) services have become one of the most essential parts to extend human capabilities in various fields such as face recognition for security, weather prediction, and so on. Various learning algorithms for existing AI services are utilized, such as classification, regression, and deep learning, to increase accuracy and efficiency for humans. Nonetheless, these services face many challenges such as fake news spread on social media, stock selection, and volatility delay in stock prediction systems and inaccurate movie-based recommendation systems. In this paper, various algorithms are presented to mitigate these issues in different systems and services. Convolutional neural network algorithms are used for detecting fake news in Korean language with a Word-Embedded model. It is based on k-clique and data mining and increased accuracy in personalized recommendation-based services stock selection and volatility delay in stock prediction. Other algorithms like multi-level fusion processing address problems of lack of real-time database.

• Asia pacific journal of information systems
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• 제34권1호
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• pp.91-113
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• 2024

In the wake of the COVID-19 pandemic, unsubstantiated information concerning vaccines and the coronavirus has proliferated on various social media platforms. Consequently, we have considered viable actions to mitigate the impact of such unverified content, enabling individuals to use social media platforms more effectively and minimize any ensuing confusion. Recent measures in this area have included YouTube's practice of labeling vaccine or corona videos as authoritative when emanating from reputable organizations and Twitter's practice of flagging vaccine-related content as potentially misleading or taken out of context. This study seeks to explore how such contrasting labeling practices influence users' believability and engagement differentially, while also examining the moderating impact of regulatory focus. The results indicate that authoritative labeling positively influenced users' believability and engagement, whereas misleading labeling adversely affected users' believability and engagement. Additionally, our findings revealed that authoritative labeling has a stronger impact on promotion-focused individuals, while misleading labeling has a more pronounced effect on prevention-focused individuals. Our findings offer insights into how social media platforms can design and present information to their users, taking into account their regulatory focus.

• Journal of Contemporary Eastern Asia
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• 제18권2호
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• pp.49-67
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• 2019

Since returning to power in 2012, the second Abe administration has pressured Japanese mainstream media in various ways, from creating the Secrecy Act to forming close relationships with media executives and promoting anti-journalism voices on social media. This article focuses on the growth of a jingoist group called the 'Net-rightists' ('Neto-uyo' in the Japanese abbreviation) on the Internet, which has been supporting the right-wing government and amplifying its historical revisionist views of Japanese colonialism. These heavy Internet users deny Japan's war crimes against neighboring Asian countries and disseminate fake news about the past, which justifies Prime Minister Shinzo Abe's hostile diplomatic policies against South Korea and China. Over the past years, the rightist online discourses have become powerful to such an extent that the editorials of major newspapers and TV reports shifted to more nationalist tones. Who are the Neto-uyo? Why have they emerged from the online world and proliferated to the offline world? Two significant characteristics of new media are discussed to analyze their successful media manipulation: cultural transcoding and perpetual rewriting of collective memories. These characteristics have resulted in constructing and reinforcing the data loops of the 'Daily Us' versus Them, technologically raising current diplomatic tensions in East Asia.

• 한국콘텐츠학회논문지
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• 제21권6호
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• pp.466-479
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• 2021

전체 또는 일부분에 사실이 아닌 거짓을 섞어 만든 가짜뉴스가 범람하고 있다. 정치·사회적인 목적의 프레임을 만들기 위해 주로 사실에 가짜를 결합하여 뉴스를 만들거나, 선동의 목적으로 왜곡과 혐오를 조장하기 위해 뉴스를 만든다. 특히 공중파 방송을 포함한 몇몇 언론이 특정한 방향의 정치적 편향성을 주저 없이 표출하고 있다. 언론이 정치적 편향성을 가지더라도 사실 전달을 기본으로 한다면, 보수와 진보의 상호견제 속에 신뢰받는 언론 환경이 이루어질 수 있을 것이다. 5·18민주화운동은 보수와 진보를 떠나서 현대사의 아픈 역사이자 사실이다. 그런데도 5·18민주화운동을 민주화운동과 폭동으로 보는 상반된 관점들이 있다. 본 연구는 보수 성향의 중앙일보 만평과 진보 성향의 경향신문 만평이 5·18민주화운동을 어떻게 다루고 있는지 분석했다. 중앙일보와 경향신문의 만평은 5·18민주화운동을 보는 관점에서 큰 차이가 있다. 진보 성향의 경향신문 만평은 사건의 본질을 드러내고 대상을 풍자하였다는 점에서 큰 의미를 가진다. 반면, 보수 성향의 중앙일보 만평은 모호성으로 인해 사건의 본질이나 풍자 대상에 대해 다가가지 못하고 있다. 5·18민주화운동을 소재로 하는 경향신문과 중앙일보 만평의 차이를 통해 보수와 진보 언론의 가치를 생각해보는 계기가 되길 바란다.

• 한국정보통신학회논문지
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• 제25권9호
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• pp.1275-1278
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• 2021

Nowadays, fake news from newspapers and social media is a serious issue in news credibility. Some of machine learning methods (such as LSTM, logistic regression, and Transformer) has been applied for fact checking. In this paper, we present Transformer-based fact checking model which improves computational efficiency. Locality Sensitive Hashing (LSH) is employed to efficiently compute attention value so that it can reduce the computation time. With LSH, model can group semantically similar words, and compute attention value within the group. The performance of proposed model is 75% for accuracy, 42.9% and 75% for Fl micro score and F1 macro score, respectively.

• 한국정보시스템학회지:정보시스템연구
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• 제31권1호
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• pp.175-195
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• 2022

Purpose The purpose of this study is to examine news articles and analyze trends and key agendas related to artificial intelligence(AI). In particular, this study tried to compare the reporting behaviors of Korea and the United States, which is considered to be a leader in the field of AI. Design/methodology/approach This study analyzed news articles using a big data method. Specifically, main agendas of the two countries were derived and compared through the keyword frequency analysis, topic modeling, and language network analysis. Findings As a result of the keyword analysis, the introduction of AI and related services were reported importantly in Korea. In the US, the war of hegemony led by giant IT companies were widely covered in the media. The main topics in Korean media were 'Strategy in the 4th Industrial Revolution Era', 'Building a Digital Platform', 'Cultivating Future human resources', 'Building AI applications', 'Introduction of Chatbot Services', 'Launching AI Speaker', and 'Alphago Match'. The main topics of US media coverage were 'The Bright and Dark Sides of Future Technology', 'The War of Technology Hegemony', 'The Future of Mobility', 'AI and Daily Life', 'Social Media and Fake News', and 'The Emergence of Robots and the Future of Jobs'. The keywords with high centrality in Korea were 'release', 'service', 'base', 'robot', 'era', and 'Baduk or Go'. In the US, they were 'Google', 'Amazon', 'Facebook', 'China', 'Car', and 'Robot'.

• 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.

• 한국콘텐츠학회논문지
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• 제22권7호
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• pp.548-562
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• 2022

본 연구는 글로벌 콘텐츠에 나타난 AI 윤리의 문제적 상황을 진단하고, 인간의 정체성을 강화하기 위한 담론이 무엇인지를 파악하고자 했다. 연구 진행을 위해 넷플릭스(Netflix) 오리지널 콘텐츠 <소셜딜레마>(The Social Dilemma)를 분석대상으로 선정했다. 연구방법은 서사분석을 채택했다. 분석결과 <소셜딜레마>는 전통적인 시사 다큐멘터리 구조를 보였으며, 이야기 전개를 위해 주로 전문가와 통계자료를 활용한 것으로 확인되었다. 미얀마 학살 사건, 가짜뉴스 전파 등 국내외 사례를 열거하며 콘텐츠 핵심 주장을 강화하기도 했다. 인물의 관계에서는 개발자와 미디어 기업, 이용자와 광고주 사이의 이항대립이 명확하게 드러났다. 해결책으로는 기업에 대한 강력한 규제와 소셜미디어의 이용 중단을 주장했다. 하지만, <소셜딜레마>는 AI 기술의 오남용을 지적하는 수준에 머무르며, 인간 고유의 정체성과 사회적 관계를 외면하는 서사를 구성했다. 이러한 결과는 AI 시대를 맞아 인간의 사회성과 관계성, 학습 능력의 중요성을 강조하는 콘텐츠의 필요성을 제기한다.