• The Journal of Society for e-Business Studies
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• v.20 no.4
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• pp.19-39
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• 2015

Internet of Things (IoT) is expected to provide efficiency and convenience in human life by integrating the Internet into the things that we use in daily lives. IoT can not only create new businesses but also can bring great changes in our lives thanks to the various ways of technical application: defining relationships among things or automatic use of technology by analyzing the usage pattern. This study uses the qualitative research of interviewing the experts to predict the changes that IoT technology is expected to bring in our lives. In addition, this paper analyzes news articles about internet of things in Korea using text-network analysis. This study also discusses the factors which need to be considered to put IoT into successful use in business contexts.

• Hwankyungkyoyuk
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• v.13 no.2
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• pp.24-37
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• 2000

Korean civil and environmental organizations had selected and announced ‘The top ten pieces of news in the environmental field of the year’ on Dec. 2, 1999. This study investigated the possibilities that these could be used as subject matters of environmental curriculum and infused into the environmental textbook of secondary schools, referring to documents and internet materials. The top ten pieces of environmental news could be clarified as controversial topics. The locality was analyzed that 2 pieces occurred mainly in a specific area, 4 pieces in several areas and 4 pieces around all over the country. Most of them had the opposing partners as the federal and local governmental vs. civil organizations and people. Each of them could be used as subject matters for 7 to 13 contents domains of the 6th and 7th Korean environmental curriculum. The knowledge of most of them had related counterpart concepts to be infused into the ‘Environmental Science’textbook for the high school students. The results suggested that more concerns and efforts are needed to deal and use these controversial issues as real world problems of Korea in the environmental education practices

• Journal of the Korean Society for information Management
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• v.27 no.4
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• pp.109-130
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• 2010

The purpose of this study is to identify th patterns in the news reporters' information seeking behaviors by observing their web activities. For this purpose, transaction logs collected from 23 news reporters were analyzed. Web tracking software was installed to collect the data from their PCs, and a total of 39,860 web logs were collected in two weeks. Start and end pattern of sessions, transitional pattern by step, sequence rule model was analyzed and the pattern of Internet use was compared with the general public. the analysis of pattern derived a web information seeking behavior modes that consists of four types of behaviors: fact-checking browsing, fact-checking search, investigative browsing and investigative search.

• Iberoamérica
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• v.16 no.2
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• pp.151-188
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• 2014

This work aims to describe pragmatic strategies and linguistic features of replies that occur in the comment section of online newspapers. The dominant media in this digital age is the Internet and its rapid development and expansion of use have contributed not only to the change of the form of production of journalistic texts, but also to the consumption of those texts. In the past, the news was transmitted in a unidirectional way but now readers of online newspapers do not remain passively reading the articles. They actively participate in the exchange of opinions with other readers. The individual consumption of journalistic texts has become a collective and social act. The purpose of the study is to investigate the communication intention of the users of comment sections and analyze the linguistic formulation of replies. We attempt to discover specific aspects of replies and responses for online newspaper articles, considering them as an independent type of Computer Mediated Communication (Internet Mediated Communication). Observing language attitudes appearing in the electronic environment and discovering the characteristics of the Spanish language on the Internet will allow us to contribute to understand the theoretical aspects related to the CMO better.

• Journal of Information Science Theory and Practice
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• v.11 no.1
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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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.1
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• pp.51-73
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• 2023

Social media play a significant role in communicating information across the globe, connecting with loved ones, getting the news, communicating ideas, etc. However, a group of people uses social media to spread fake information, which has a bad impact on society. Therefore, minimizing fake news and its detection are the two primary challenges that need to be addressed. This paper presents a multi-modal deep learning technique to address the above challenges. The proposed modal can use and process visual and textual features. Therefore, it has the ability to detect fake information from visual and textual data. We used EfficientNetB0 and a sentence transformer, respectively, for detecting counterfeit images and for textural learning. Feature embedding is performed at individual channels, whilst fusion is done at the last classification layer. The late fusion is applied intentionally to mitigate the noisy data that are generated by multi-modalities. Extensive experiments are conducted, and performance is evaluated against state-of-the-art methods. Three real-world benchmark datasets, such as MediaEval (Twitter), Weibo, and Fakeddit, are used for experimentation. Result reveals that the proposed modal outperformed the state-of-the-art methods and achieved an accuracy of 86.48%, 82.50%, and 88.80%, respectively, for MediaEval (Twitter), Weibo, and Fakeddit datasets.

• Journal of Internet Computing and Services
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• v.16 no.3
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• pp.105-116
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• 2015

The Sewol ferry catastrophe that took place on April 16 2014 was unprecedented in terms of its sociopolitical implications, which had reverberated throughout the Korean nation. Mindful of such distinct characteristics of the Sewol ferry catastrophe, this thesis looks into the salience of the agendas portrayed in Twitter and Portal News coverage on the disaster and the correlation between the attribute-specific agendas of the foregoing mediums by making use of the agenda rank order correlation method. Extraction and analysis of big data revealed that first, while the hypothesis that there were little difference in terms of salience among the main agendas between Twitter and Portal News was dismissed, the rank order correlation proved to be high as regards the main agendas on Twitter and Portal News. This signifies that Twitter agendas exert influence over those on Portal News. Next, and regarding the five main agendas on the incident, there existed differences in salience between the attribute-specific agendas of the two mediums, with low figures for corresponding rank order correlations. Such results signify that Twitter and Portal News have little influence over each other as regards their agenda rank order correlation.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.197-216
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• 2022

With the development of Internet and mobile technology and the spread of social media, a large amount of information is being generated and distributed online. Some of them are useful information for the public, but others are misleading information. The misleading information, so-called 'fake news', has been causing great harm to our society in recent years. Since the global spread of COVID-19 in 2020, much of fake news has been distributed online. Unlike other fake news, fake news related to COVID-19 can threaten people's health and even their lives. Therefore, intelligent technology that automatically detects and prevents fake news related to COVID-19 is a meaningful research topic to improve social health. Fake news related to COVID-19 has spread rapidly through social media, however, there have been few studies in Korea that proposed intelligent fake news detection using the information about how the fake news spreads through social media. Under this background, we propose a novel model that uses Graph2vec, one of the graph embedding methods, to effectively detect fake news related to COVID-19. The mainstream approaches of fake news detection have focused on news content, i.e., characteristics of the text, but the proposed model in this study can exploit information transmission relationships in social engagement networks when detecting fake news related to COVID-19. Experiments using a real-world data set have shown that our proposed model outperforms traditional models from the perspectives of prediction accuracy.

• Journal of the Korean Society for information Management
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• v.19 no.4
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• pp.185-208
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• 2002

Information service for the aged is a new challenge for public libraries in Korea. To develop an internet-based information service at public library perspectives, information sources, information need, and information seeking and using behavior are investigated. Interview survey is performed to 1060 adults aged 60 and over. Finding revealed that the respondents led to few channels to information except for mass media and informal oral communication. It ascertain ways in which 23% of the respondents currently use internet, and identify barriers of nonusers. The information need of the elderly are diverse, but health/medicine, news, hobbies, religion, leisure/travel are most identified need in descending order. Based on data analysis and previous research results, a cooperative service model consisting of information contents, online reference, interface design, and education is developed. Finally problems and suggestions for future improvement are discussed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.1
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• pp.391-406
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• 2015

Social media have emerged as new communication channels between consumers and companies that generate a large volume of unstructured text data. This social media content, which contains consumers' opinions and interests, is recognized as valuable material from which businesses can mine useful information; consequently, many researchers have reported on opinion-mining frameworks, methods, techniques, and tools for business intelligence over various industries. These studies sometimes focused on how to use opinion mining in business fields or emphasized methods of analyzing content to achieve results that are more accurate. They also considered how to visualize the results to ensure easier understanding. However, we found that such approaches are often technically complex and insufficiently user-friendly to help with business decisions and planning. Therefore, in this study we attempt to formulate a more comprehensive and practical methodology to conduct social media opinion mining and apply our methodology to a case study of the oldest instant noodle product in Korea. We also present graphical tools and visualized outputs that include volume and sentiment graphs, time-series graphs, a topic word cloud, a heat map, and a valence tree map with a classification. Our resources are from public-domain social media content such as blogs, forum messages, and news articles that we analyze with natural language processing, statistics, and graphics packages in the freeware R project environment. We believe our methodology and visualization outputs can provide a practical and reliable guide for immediate use, not just in the food industry but other industries as well.