• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.11
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• pp.2966-2986
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• 2023

Climate change is a constant threat to human life, and it is important to understand the public perception of this issue. Previous studies examining climate change have been based on limited survey data. In this study, the authors used big data such as news articles and social media data, within which the authors selected specific keywords related to climate change. Using these natural language data, topic modeling was performed for discourse analysis regarding climate change based on various topics. In addition, before applying topic modeling, sentiment analysis was adjusted to discover the differences between discourses on climate change. Through this approach, discourses of positive and negative tendencies were classified. As a result, it was possible to identify the tendency of each document by extracting key words for the classified discourse. This study aims to prove that topic modeling is a useful methodology for exploring discourse on platforms with big data. Moreover, the reliability of the study was increased by performing topic modeling in consideration of objective indicators (i.e., coherence score, perplexity). Theoretically, based on the social amplification of risk framework (SARF), this study demonstrates that the diffusion of the agenda of climate change in public news media leads to personal anxiety and fear on social media.

• Korea Journal of Hospital Management
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• v.4 no.2
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• pp.60-84
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• 1999

Hospitals under competitive environment are getting more interested in PR(public relations) as a means of marketing. A typical form of public relations for the hospital is publicity, and its principal instrument is the press release that provides the mass media with the raw material and background for a news story. The purpose of this paper is to examine and analyze the public relations articles associated with hospitals in the section of health care in major daily newspapers. Three major daily newspapers, Chosun, Joongang and Hankyoreh have been analyzed for a year from January 1, 1998 to December 31, 1998. All articles in the health care section are classified by content, size, press comments, and style. This study has found some perverse aspects of the public relations such as the preponderance of health articles on tertiary medical institutions, inappropriate publicity focused on certain medical treatments, doctors, and hospitals, and the positive press comments on the hospitals that are affiliated with the same corporate group as the newspaper.

• Journal of the Korean Society for information Management
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• v.35 no.1
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• pp.231-250
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• 2018

In this paper, we propose a new methodology for extracting and formalizing subjective topics at a specific time using a set of keywords extracted automatically from online news articles. To do this, we first extracted a set of keywords by applying TF-IDF methods selected by a series of comparative experiments on various statistical weighting schemes that can measure the importance of individual words in a large set of texts. In order to effectively calculate the semantic relation between extracted keywords, a set of word embedding vectors was constructed by using about 1,000,000 news articles collected separately. Individual keywords extracted were quantified in the form of numerical vectors and clustered by K-means algorithm. As a result of qualitative in-depth analysis of each keyword cluster finally obtained, we witnessed that most of the clusters were evaluated as appropriate topics with sufficient semantic concentration for us to easily assign labels to them.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.27 no.2
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• pp.81-94
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• 2016

This study analyzes the problems in reading program of public libraries and provides some suggestions for the program development and management. For this analysis, I sampled and examined 350 news articles to reading programs done in the public libraries between 2013 and 2015. The result shows that 41.4% of the collected articles were the news about the reading programs in Seoul Metropolitan areas. While the articles about simple reading programs occupied 69.9%, the mixed activity programs reached a significant amount in total. In addition, 51.3% of program participants was under the elementary children and their parents, but only 9.0% program participants came from low socioeconomic status classes. 86 reading programs (28.4%) were designed for one-day events without a long-term policy. Based on such analyses, this study provides three suggestions: utilizing public relation teams and communicating mass media to advertize reading programs to local residents, developing systematic reading programs in users' needs, managing the reading programs for all kinds of local residents.

• Journal of the Korean Society for information Management
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• v.39 no.2
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• pp.275-298
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• 2022

This study examined the issues and characteristics that appeared in news and journal articles related to the 'right to be forgotten' using text mining analysis. Data for analysis were collected from 2010 to 2020 with the keyword 'right to be forgotten'. Keyword analysis and topic modeling analysis were performed on the collected data. As a result, in the last 10 years the issues about 'right to be forgotten' are not much different in news and journal articles and the approaches also are similar. However, it confirmed common issues and the partial difference between news and journal articles through comparison. Therefore in Archives and Records Management Studies, it is necessary to discuss derived in this study. In particular common issues are considered first but if there are differences in issues, it is needed to discuss them in various ways. This study is meaningful to understand the meaning and to draw issues that may arise in the future of the 'right to be forgotten'. The results of this study will contribute to be variously discussed on the 'right to be forgotten' in Archives and Records Management Studies.

• Journal of KIISE:Computing Practices and Letters
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• v.7 no.5
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• pp.416-428
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• 2001

In order to build a news archive system. the news video stream should be first segmented into several articles, ad their contents are abstracted effectively. This abstraction helps the users to understand the contents of the article without playing the whole video stream. This paper proposes a new article boundary detection scheme for the news video streams together with a new news article abstraction scheme using the shot types of the news video data. The shots in the news video are classified into anchor person shots, interview shots, speech shots, reporting shots, graphic shots, and others. Since the news article starts with an anchor shot whose duration is relatively longer than other shots with special screen structure, the article boundary in detected by the computing the length of the shot and checking the screen structure in the proposed scheme. For the effective abstraction of the article video, the graphic image located in the right-top of the anchor shot frames is primarily used in the proposed abstraction scheme since it is the abstraction of the article made by the producer of the news according to its contents so that it contains a lot of meaningful information. The key frames of the other shots except interview and report shots are also used to abstract the contents of the articles in the proposed scheme. Upon experimental results, the precision and recall values of the proposed article boundary detection scheme could be 92% and 96%, respectively. This paper also presents a design and implementation of a prototype news archive system on WWW that consists of an indexing tool, an authoring tool, a database for meta-data of the news, and a browsing tool.

• Korean journal of communication and information
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• v.34
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• pp.132-160
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• 2006

The main purpose of this study is based on the comparative analysis over news framing of the family headship(Hoju) abolition in Korean society. This study examined the newspaper articles involving the Hoju abolition, which had been printed on the three major dailies, Chosun, Kukmin, Hankyoreh through February of 1990 to July of 2005. First, the news articles were analyzed and classified on the basis of their lengths, news types, main characters, news framing and systematic framing. Second, the articles that this study looked into were divided into the five major periods when the issue of the Hoju abolition in Korean society surfaced as a main social agenda to be discussed. Third, the main differences between the noticeable frame and unnoticeable frame in each period were analyzed through the three different perspectives which can also can be sub-divided into the six different attributes. This study found that the Hoju abolition as an attribute had developed into political, legal and social fields. The analysis of the research shows that the articles related to the patriarchy abolition showed more dominant frame which reflected the social change or the general tendency of the times. However, the analysis indicates that the articles in the level of an attribute included more dominant frame which mirrored a male chauvinism society. It also points out that the articles contained more dominant frame which was be used as a standard to find out the readers' political inclination. The articles also showed the dominant frame which included the revision and legal process of family laws before presidential or general election campaigns. The study also found that there were major differences among the three dailies. First of all, Chosun, regarded the Hoju as a custom by stressing that 'it is necessary to keep Hoju system to intensify the role and crisis of family if the Hoju will be abolished'. However, Hankyoreh recognized the issue as an important one to improve feminism and female rights by maintaining that 'it is the time to balance the inequality out between men and women with the abolition of patriarchy'. Finally, Kukmin treated the issue as an first step to acknowledge the dignity of females by emphasizing that 'a revision of the law is essential to accept the changing ethics of the times'.

• Journal of Society of Preventive Korean Medicine
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• v.21 no.2
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• pp.95-103
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• 2017

Objectives : The aim of this study is to analyze the news contents of Korean style medicinal tea and investigate how it is portrayed in the consumer market. Methods : Total of 355 articles are selected by inputting "Korean style medicinal tea" and analyzed; 108 articles for 2013, 107 articles for 2014, 140 articles for 2015. Results : 175 different tea were found from Jan. $1^{st}$ 2013 to Dec. $31^{st}$ 2015, with ginger tea the most frequently covered for 68 times. Among 175 tea, 117 had one ingredient and 58 had more than one ingredient. The most frequently covered category was "Disease and Health Promotion" followed by "Commercial Ads", "Korean style medicinal tea Culture", and others. From 355 articles, 188 provided the information on the efficacy of Korean style medicinal tea, 88 presented the pharmacological activity, 84 addressed the recipe, 80 explained the taste, and 31 included ancient literature. The most frequently covered tea were ginger tea, omija tea, gugija tea, jujube tea, mogwa tea. Autumn and winter had 109 articles, spring had 89, and summer had 86. Conclusions : This study showed the potential of Korean style medicinal tea as a successful future content. Most of the articles about Korean style medicinal tea contained information about the efficacy but practical information such as the recipe and drinking method were not addressed much. Therefore, future study is needed to investigate additional information about Korean style medicinal tea.

• The Journal of Information Systems
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• v.31 no.1
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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'.

• Journal of Information Technology Applications and Management
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• v.25 no.1
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• pp.19-32
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• 2018

Fake news is defined as the news articles that are intentionally and verifiably false, and could mislead readers. Spread of fake news may provoke anxiety, chaos, fear, or irrational decisions of the public. Thus, detecting fake news and preventing its spread has become very important issue in our society. However, due to the huge amount of fake news produced every day, it is almost impossible to identify it by a human. Under this context, researchers have tried to develop automated fake news detection method using Artificial Intelligence techniques over the past years. But, unfortunately, there have been no prior studies proposed an automated fake news detection method for Korean news. In this study, we aim to detect Korean fake news using text mining and machine learning techniques. Our proposed method consists of two steps. In the first step, the news contents to be analyzed is convert to quantified values using various text mining techniques (Topic Modeling, TF-IDF, and so on). After that, in step 2, classifiers are trained using the values produced in step 1. As the classifiers, machine learning techniques such as multiple discriminant analysis, case based reasoning, artificial neural networks, and support vector machine can be applied. To validate the effectiveness of the proposed method, we collected 200 Korean news from Seoul National University's FactCheck (http://factcheck.snu.ac.kr). which provides with detailed analysis reports from about 20 media outlets and links to source documents for each case. Using this dataset, we will identify which text features are important as well as which classifiers are effective in detecting Korean fake news.