• Journal of Korea Society of Industrial Information Systems
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• v.18 no.2
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• pp.47-57
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• 2013

Today a lot of functional areas of a firm are operated on the Web. Online shopping malls analyze web log recording customers' activities on the web to connect them to business outcomes. Not only commercial websites, but online news sites also need to collect and analyze web logs to understand their news readers' interest. However, little research has been performed yet. In this research we mined the web access log of an online news website and conduct Market Basket Analysis to uncover the association rules among the categories of news articles. The research is composed of two stages: 1) Identifying the individual session of a visitor; 2) Mining association rule from news articles read by each session. We gather 7-day access logs two times. The results of log mining and meanings of association rules are suggested with managerial implications in conclusion section.

• Journal of Industrial Convergence
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• v.20 no.12
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• pp.135-143
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• 2022

This paper aims to grasp what propensity users have in their ideology from the comments in the Web Portal News and the Press Website News. Through these analytical results, the political propensities of not only the Web Portal News and the Press Website News but also the voters who use these news media could be grasped. The collection of data necessary for this study has been made from the comments of 174 news stories for about 90 days before the election day. For the analysis, T-test has been used in order to compare Naver News with Daum News, the Minjoo Party of Korea with the People Power Party, and the Press Web Site News with Naver News. As a result of the analysis, the comments of Naver News took the higher percentage in the positive writings about the candidates of the conservative party. but, in contrast, those of Daum News in that percentage were higher about the ones of the progressive party. Accordingly, it can be found that Naver News is mainly used by users with the politically conservative propensity, while Daum News is mostly used by those with progressive one.

• Asia pacific journal of information systems
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• v.31 no.4
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• pp.606-632
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• 2021

With many consumers being exposed to news via social media platforms, news organizations are challenged to attract visitors and generate revenue during visits to their websites. They therefore need detailed information on how to write articles and headlines to increase visitors' engagement with the content to drive advertising revenues. For those news organizations whose business model depends mainly on advertisements, rather than subscriptions, it is particularly crucial to understand what makes the website attractive to their visitors, what drives users to stay on the website, and what factors affect a user's exit decision. The current research examines individual news consumers' choices to find patterns of increase or decrease in user engagement relative to a variety of topics, as well as to the mood or tone of the content. Using clickstream data from a major news organization, the authors develop a user-level dynamic model of clickstream behavior that takes into account the content of both headlines and stories that visitors read. The authors find that readers appear to exhibit state dependence in the tone of the articles that they read. They also show how the topics expressed in headlines can affect the amount of content readers consume when visiting the news organization to a much larger degree than the topics expressed in the content of the article. Online publishers can make use of such findings to present visitors with content that is likely to maintain and/or increase their engagement and consequently drive advertising revenue.

• Journal of Information Technology Services
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• v.16 no.4
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• pp.177-195
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• 2017

Traditionally, news was consumed only through printed newspapers and broadcasting media, such as radio and television. However, the Internet has enabled people to consume news content online. Since most of online news content has been provided for free, it is not easy for news providers to charge the fixed subscription fee for online news content. Therefore, as an alternative strategy, some online news providers have tried to adopt the Pay-What-You-Want (PWYW) pricing model, which allows users (readers) to pay as much as they want after consuming news content. As this pricing model shows some possibility to grow and replace the unsuccessful monetization strategy of online news content, we therefore examined the comparative importance of seven heuristic attributes (i.e., article evaluation, article share, article comment, article information design, article length, writer SNS, and writer information) affecting readers' voluntary payment behavior through a conjoint analysis with 379 news articles collected from online news Website (i.e., Ohmynews.com) where the PWYW model has been working successfully. This study found that article share and article length are the most important factors which affect online news content users' voluntary payment. Finally, two major and eight minor propositions are suggested based on the findings of the study. This study would suggest guidelines for how to create online news content which induces much more voluntary payment.

• Korean journal of communication and information
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• v.45
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• pp.463-495
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• 2009

Korea has started to pay attention to civic journalism in recent years while it initially emerged in the United State since late 1980s. Furthermore, albeit some discernable limitations, the Internet has played an important role in fertilizing civic journalism as indicated by the emergence of online news media and the increasing number of civic journalists engaged in the online activities. Whereas there are some patterns of civic journalism practice and the civic influence commonly observed in both countries, there are significant factors that distinguish th1e case of Korea from that of the U.S. The purpose of this study is to compare the two countries in terms of the patterns of civic journalism practice and civic influence. This goal has been achieved by analyzing ‘CNN iReport’ in the U.S. and ‘Ohmynews’ in Korea, both of which are prime civic journalism websites. Those websites have been compared in light of four standards of civic journalism: first, the degree of post-objectivism; second, the search for effective resolutions of social problems; third, civic engagement in the news making process to enhance bottom-up agenda setting; and finally, citizens’ interaction with the news. The results reveal that the American civic journalism website is more likely to shed light on deviating from the principle of objectivity and seeking alternatives and resolutions of social problems. Moreover, it effectively utilizes civic engagement in the news Abstracts 551 making process as indicated by the higher numbers of civic journalists and civic news resources. Also, readers’ interaction with the news was found to be more active in the iReport website than in the Ohmynews.

• International Commerce and Information Review
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• v.17 no.1
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• pp.3-28
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• 2015

Web-ads often distract users' online activities. Web-ads even deter users from comprehending the website contents. As these irritated users try to avoid web-ads, advertising agencies make web-ads even more noticeable to grasp users' attention. The factors that attract users should increase web-ad performance. However, this study confirms that those efforts irritate users and decrease web-ad performance. Also, this study shows that irritated users eventually try to avoid re-visiting the websites. This study also confirms that excessive web-ads on Internet news websites bring more confusion to users than on e-commerce websites. This finding supports the importance of more sustainable web activities on the Internet news websites as users expect objective and fair contents. Based on these results, this study proposes the directions of web-ads activities for the common good and self-interests of the stakeholders.

• YAKHAK HOEJI
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• v.56 no.3
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• pp.204-209
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• 2012

The purpose of this study was to construct database for a drug safety information website to serve as an access point of up-to-date resources for a wide variety of drug-safety information helping patients and healthcare professionals make well-informed decisions about medication use. All the contents developed were confirmed by the council of advisors who were the experts in drug safety. The detailed contents of database on frequently prescribed drug including 9 NSAIDs, 19 antibiotics, 24 cardiovascular, 21 metabolic, 14 respiratory, 20 digestive, 22 hormonal, 10 genitourinary, 10 anti-allergic, 27 antifungal/antiviral, and 71 neuropsychiatric agents were developed based on the approved drug labeling of the Korean FDA. A separately searchable database of drug-specific safety information for patients and health professionals was constructed for users in need of different depth of knowledge on using medications safely. The safety information on highly prevalent chronic diseases and drug classes was also developed. Finally the most recent global drug safety news was provided. The consumer directed information was developed in layman's terms as means of proving user-friendly information. The creation of this type of website is part of the Korean FDA's ongoing initiative to address and promote the safe use of medications for the public.

• Journal of The Korean Association of Information Education
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• v.25 no.6
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• pp.935-945
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• 2021

The purpose of this study is to analyze the social perception of Arduino lecture using big data analysis method. For this purpose, data from January 2012 to May 2021 were collected using the Textom website as a keyword searched for 'arduino + lecture' in blogs, cafes, and news channels of NAVER website. The collected data was refined using the Textom website, and text mining analysis and semantic network analysis were performed by opening the Textom website, Ucinet 6, and Netdraw programs. As a result of text mining analysis such as frequency analysis, TF-IDF analysis, and degree centrality it was confirmed that 'education' and 'coding' were the top keywords. As a result of CONCOR analysis for semantic network analysis, four clusters can be identified: 'Arduino-related education', 'Physical computing-related lecture', 'Arduino special lecture', and 'GUI programming'. Through this study, it was possible to confirm various meaningful social perceptions of the general public in relation to Arduino lecture on the Internet. The results of this study will be used as data that provides meaningful implications for instructors preparing for Arduino lectures, researchers studying the subject, and policy makers who establish software education or coding education and related policies.

• Atmosphere
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• v.30 no.3
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• pp.237-248
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• 2020

In order to effectively prepare for damage caused by weather events, it is important to proactively identify the possible impacts of weather phenomena on the domestic society and economy. Text mining and Network analysis are used in this paper to build a database of damage types and levels caused by heat wave. We collect news articles about heat wave from the SBS news website and determine the primary and secondary effects of that through network analysis. In addition to that, based on the frequency with which each impact keyword is mentioned, we estimate how much influence each factor has. As a result, the types of impacts caused by heat wave are efficiently derived. Among these types of impacts, we find that people in South Korea are mainly interested in algae and heat-related illness. Since this technique of analysis can be applied not only to news articles but also to social media contents, such as Twitter and Facebook, it is expected to be used as a useful tool for building weather impact databases.

• The Korean Journal of Applied Statistics
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• v.34 no.1
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• pp.57-74
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• 2021

The proliferation of smart devices (such as smart phones and tablet PCs) has led to a marked increase in the use of mobile-based internet. As a result, the influence of the mobile internet has become important to make opinions on social issues. This study explores the effects of mobile internet news users' characteristics on formation of opinions about major political, economic and social issues. We used the data from the media audience awareness survey by the Korean Press Foundation in 2016 and 2017 in this analysis. The characteristics of the news users are gender, age, education, income, news usage days, news usage hours, media application usage days, news gathering application usage days, portal usage days, and media official website usage days. These characteristics are known as possible explanatory variables for the mobile internet news users. Multiple logistic regressions were done with interpretation to know which covariates affect on formation of major opinion.