• International Journal of Computer Science & Network Security
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• v.24 no.6
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• pp.1-7
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• 2024

Comparing text features involves evaluating the "similarity" between texts. It is crucial to use appropriate similarity measures when comparing similarities. This study utilized various techniques to assess the similarities between newspaper articles, including deep learning and a previously proposed method: a combination of Pointwise Mutual Information (PMI) and Word Pair Matching (WPM), denoted as PMI+WPM. For performance comparison, law data from medical research in Japan were utilized as validation data in evaluating the PMI+WPM method. The distribution of similarities in text data varies depending on the evaluation technique and genre, as revealed by the comparative analysis. For newspaper data, non-deep learning methods demonstrated better similarity evaluation accuracy than deep learning methods. Additionally, evaluating similarities in law data is more challenging than in newspaper articles. Despite deep learning being the prevalent method for evaluating textual similarities, this study demonstrates that non-deep learning methods can be effective regarding Japanese-based texts.

• Journal of Preventive Medicine and Public Health
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• v.36 no.3
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• pp.298-301
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• 2003

Objectives : There is an increasing concern for the social, economic, environmental and health effects of the Asian dust (Hwang-sa in Korean language) in Korea. In this study, we intended to indirectly determine ordinary people's perception about the Asian dust by analyzing the contents of newspaper articles dealing with it. Methods: By using article searching services in the internet websites of three newspaper companies, we collected newspaper articles dealing with the Asian dust during the period from January $1^{st}$ of 1998 to December $31^{st}$ of 2002. We classified the articles into four categories: those forecasting the occurrence of the Asian dust, those about measures to cope with it, those about its occurrence in the neighboring foreign countries, and those about its effects. In particular, we analyzed articles about the health effects of the Asian dust more distinctly. Results : A total of 1,225 articles dealing with the Asian dust were found during the 5 year period. The number of articles increased from 102 in 1998 to 518 in 2002, approximately a five-fold increase, The numbers of articles about health effects, environmental effects and economical effects were 191 (44%), 171 (41%) and 147 (34%), respectively. It was reported that various diseases such as respiratory diseases (87%), eye problems (69%), and skin diseases (12%) were associated with the Asian dust. Conclusion : The increasing concern for the negative effects of the Asian dust necessitates more studios about this field. As the effects of the Asian dust are various, the information on the major concern of ordinary people could help establish the research agendas and measures for the Asian dust.

• Journal of Digital Convergence
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• v.20 no.1
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• pp.1-13
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• 2022

This study aims to examine the trend and characteristics of newspaper articles concerned with fine particle matter. Newspaper articles since 1995 collected from Bigkinds were analyzed using text mining techniques, sentiment analysis and regression analysis. Air pollution measurement and domestic pollutants appeared frequently previously, but "China" became the keyword in the 2010s along with political action, the effects on the health, AD/PR, and domestic pollutants. Korea JoongAng Daily, Hankyoreh and Kyunghyang Shinmun have had more focused on political regulations whereas most regional daily newspapers on emission sources and reduction measures at the regional level. The results of this study are expected to be used as a reference for understanding the trend of newspaper articles. Future work includes further analysis and discussion of fine particle pollution condition and news reports in the post-COVID era.

• Journal of the Korean Society for Library and Information Science
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• v.46 no.1
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• pp.223-240
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• 2012

This study aimed to enhance our understanding of the public relations of public libraries through newspaper article analysis. Thus, this study built a theoretical background on the public relations of public libraries through newspaper articles. It examined newspaper articles on Eunpyeong Public Library in 2010 according to newspaper classification, article type, and article content among others. Accordingly, this exploratory case study, which used the methods of content analysis, interview, and site visit, analyzed them, with emphasis on such factors as the subjects, objects, direction, contents, and methods that influenced the public relations of public libraries.

• Journal of information and communication convergence engineering
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• v.18 no.4
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• pp.216-221
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• 2020

Artificial intelligence (AI), an essential skill of the Fourth Industrial Revolution, is being actively taught in higher education; however, AI education is only in the preparatory stage in elementary, middle, and high schools. Investigating various newspaper articles related to AI education to date can aid in basic data collection, which is an important process in the preparatory stage. Accordingly, 13,378 newspaper articles were collected from a total of 21 newspapers, and five topics were extracted using the latent Dirichlet allocation (LDA)-based topic model along with frequency analysis. Newspaper articles from the early 2000s expanded to technologies related to the Fourth Industrial Revolution. Accordingly, education in AI fields should be linked with education in AI-based technology. In addition, efforts should be made to secure the continuity and sequence of AI education in cooperation with related higher institutions and companies.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.375-384
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• 2021

This study explored the change in keywords and topics in newspaper articles related to schizophrenia after the Gangnam murder case. The study examined newspaper articles related to schizophrenia for five years before and after the Gangnam murder case. A semantic network analysis was conducted using the NetMiner 4.4.1 program. 610 articles between 2013 and 2018 were retrieved from 8 national newsletters. The most frequent core keyword was 'treatment' before the murder case, but 'incidents' after the case. Four topics were identified: 'becoming chronic if missing the time of treatment due to prejudice', 'being curable with early treatment', 'living an ordinary life with medication', 'being indicted as a murderer while impaired by a mental disorder' before the murder case. After the case, four topics were identified: 'committing murder for delusions, not misogyny', 'medication non-adherence leads to more impulsive behavior', 'claiming leniency for criminals due to the mental impairment', 'killing the police who were mobilized to stop stabbing rampage'. These findings suggest that newspaper articles should provide accurate information about schizophrenia to reduce prejudice and stigma toward patients with schizophrenia and other forms of mental illness.

• Korean Medical Education Review
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• v.24 no.2
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• pp.103-112
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• 2022

The purpose of this study was to explore, using topic modeling, the social value of doctors and medicine demanded by society as reflected in published newspaper articles in Korea. Ultimately, this study aimed to reflect social needs in the process of developing the Patient-Centered Doctor's Competency Framework in Korea. For this purpose, a total of 2,068 newspaper articles published from 2016 to 2020 were analyzed. Through topic modeling of these newspaper articles over the past 5 years, 18 topics were derived and divided into four categories. Focusing on the derived topics and keywords, the topics derived in specific years and the proportion of topics by year were analyzed. The results of this study make it possible to grasp the needs of society projected through the press for doctors and medicine. Due to the nature of the press, topics that frequently appeared in newspaper articles were mainly social phenomena related to requirements for doctors, particularly dealing with economic and legal aspects. In particular, it was confirmed that doctors are now required to have a wider range of competencies that go beyond their required medical knowledge and clinical skills. This study helped to establish doctor's competencies by analyzing social needs for doctors through the latest research methods, and the findings could help to establish and improve doctor's competencies through ongoing research in the future.

• Journal of the Korean Society of Food Culture
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• v.21 no.3
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• pp.233-240
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• 2006

This study was intended to help children to cultivate and develop a sound attitude toward food consumption and eating habits through the analysis of food and nutritional information in news articles and advertisements in three major daily children's newspapers in Korea: The Chosen Children's Daily Newspaper, The Hankook Children's Daily Newspaper, and The Donga Children's Daily Newspaper. The monitoring period was for twelve months, January to December 2003. Two hundred seventy-nine articles and three hundred thirty-five advertisements were analyzed. The results were as follows. 'Cooking and health' were the most frequent subject in food and nutrition articles. The articles' contents are evaluated positively in morality and explanation; but negatively in fairness, specialization, and objectiveness. The articles were insufficient in the explanation of professional terms, scientific bases, and practical measures for real life. It therefore seems that they were difficult for children to understand well. The most frequent themes in the advertisements were 'processed fats and sugars' such as chocolate, candies, and cookies. Frequently, they were exaggerated and accompanied by phrases promoting consumption. They did not provide sufficient well-grounded information, and focused too much on events or gifts to instigate consumer sentiment. In conclusion, the most serious problem was that most food and nutrition information in these children's newspapers was lacking in specialization. More specialized and objective information should be provided in order to enhance the educational value of children's newspapers and their utilization in school education programs. Continuous monitoring should be carried out to discover those news articles and advertisements that contain correct food and nutrition information.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.10
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• pp.731-738
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• 2013

We analyze public opinion via a sentiment analysis of tweets collected by using recent topic keywords extracted from newspaper articles. Newspaper articles collected within a certain period of time are clustered by using K-means algorithm and topic keywords for each cluster are extracted by using term frequency. A sentiment analyzer learned by a machine learning method can classify tweets according to their polarity values. We have an assumption that tweets collected by using these topic keywords deal with the same topics as the newspaper articles mentioned if the tweets and the newspapers are generated around the same time. and we tried to verify the validity of this assumption.

• Korea Trade Review
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• v.46 no.4
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• pp.61-76
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• 2021

This study focuses on three logistics-related news (Logistics Newspaper, Korea Shipping Gadget, and Korea Shipping Newspaper) in order to present changes in logistics issues, centering on Corona 19, which has recently had the greatest impact in the world. For data collection, two-year news articles in 2019 and 2020 (title, article, content, date, article classification, article URL) were collected through web crawling (using Python's BeautifulSoup, requests module) on the homepages of three representative logistics-related media companies. As for the data analysis methods, fundamental statistical analysis, Latent Dirichlet Allocation (LDA) for topic modeling, and Scattertext were performed. The analysis results were as follows. First, among the three news media related to logistics, the Korea Shipping Newspaper was carrying out the most active media activities. Second, through topic modeling with LDA, eight logistics-related topics were identified, and keywords and significant issues of each topic were presented. Third, the keywords were visually expressed through Scattertext. This is the first study to present changes in the logistics field, focusing on articles from representative logistics-related media in 2019 and 2020. In particular, 2019 and 2020 can be divided into before and after the outbreak of Corona 19, which has had a great impact not only on the logistics field but also on our lives as a whole. For future work, a multi-faceted approach is required, such as comparative studies of logistics issues between countries or presenting implications based on long-term time-series articles.