• Title/Summary/Keyword: Online Articles

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Sports Celebrities as a Determinant of Sport Media Distribution Contents: Focusing on Tacit Premise of Agenda Setting Theory (스포츠미디어의 유통 콘텐츠 결정요인으로서 스포츠 스타: 의제설정 이론의 암묵적 전제를 중심으로)

  • YOO, Sang-Keon;KIM, Yong-Eun;SEO, Won-Jae
    • Journal of Distribution Science
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    • v.17 no.10
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    • pp.83-91
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    • 2019
  • Purpose - Media is a significant distributional channel in sport. In terms of determining the influencer in building sport media contents, recent sport media studies have employed agenda-setting theory, assuming media itself as the agenda provider. In a real-world situation, however, sports stars have been deemed key factor determining distribution contents in sport. The starting point of this study is the "tacit premise" of agenda-setting theory. Given the agenda-setting theory, the current study attempted to explore the function of sport stars as an agenda provider, which is a key determinant of sport distribution. Research design, data, and methodology - This study has reviewed articles of Yuna Kim, Sang-hwa Lee, and Hyun-jin Ryu from daily newspapers including as dong-a ilbo and joongang ilbo (2013 to 2017). The study collected data, portable document format (PDF), from the online archive of dong-a ilbo and joongang ilbo. We coded the length of the article, the frequency, the size of the picture, and the structural form of the article. Inter-coder reliability was compared with data previously investigated by the researcher. Inter-coder reliabilities for study 1 and 2 was .89 and .85. To examine hypotheses, descriptive analysis, correlations, and cross-tap analysis were performed. Results - The results partially supported the hypotheses proposing the significant role of sports stars as the agenda setters in distributing sport media contents. In specific, the study found that the number of articles about sports stars prevailed the number of articles about regular athletes. Besides, studies found that the use of photos was more frequent in articles of sports starts than that of regular athletes. In sports newspaper articles, featured story articles were used more than straight-articles for news relating to sports stars. Also, sports newspaper of sports stars contained more information associated within an event rather than outside of an event. Conclusions - In sports journalism, this study challenges the current theory that the media affects the composition and the content of sports coverages. As the principle of the agenda-setting of sports media, the influence of sports stars must be continuously studied along with a follow-up study.

A Study on Automatic Classification of Newspaper Articles Based on Unsupervised Learning by Departments (비지도학습 기반의 행정부서별 신문기사 자동분류 연구)

  • Kim, Hyun-Jong;Ryu, Seung-Eui;Lee, Chul-Ho;Nam, Kwang Woo
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.9
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    • pp.345-351
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    • 2020
  • Administrative agencies today are paying keen attention to big data analysis to improve their policy responsiveness. Of all the big data, news articles can be used to understand public opinion regarding policy and policy issues. The amount of news output has increased rapidly because of the emergence of new online media outlets, which calls for the use of automated bots or automatic document classification tools. There are, however, limits to the automatic collection of news articles related to specific agencies or departments based on the existing news article categories and keyword search queries. Thus, this paper proposes a method to process articles using classification glossaries that take into account each agency's different work features. To this end, classification glossaries were developed by extracting the work features of different departments using Word2Vec and topic modeling techniques from news articles related to different agencies. As a result, the automatic classification of newspaper articles for each department yielded approximately 71% accuracy. This study is meaningful in making academic and practical contributions because it presents a method of extracting the work features for each department, and it is an unsupervised learning-based automatic classification method for automatically classifying news articles relevant to each agency.

Analysis of Topics Related to Population Aging Using Natural Language Processing Techniques (자연어 처리 기술을 활용한 인구 고령화 관련 토픽 분석)

  • Hyunjung Park;Taemin Lee;Heuiseok Lim
    • Journal of Information Technology Services
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    • v.23 no.1
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    • pp.55-79
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    • 2024
  • Korea, which is expected to enter a super-aged society in 2025, is facing the most worrisome crisis worldwide. Efforts are urgently required to examine problems and countermeasures from various angles and to improve the shortcomings. In this regard, from a new viewpoint, we intend to derive useful implications by applying the recent natural language processing techniques to online articles. More specifically, we derive three research questions: First, what topics are being reported in the online media and what is the public's response to them? Second, what is the relationship between these aging-related topics and individual happiness factors? Third, what are the strategic directions and implications for benchmarking discussed to solve the problem of population aging? To find answers to these, we collect Naver portal articles related to population aging and their classification categories, comments, and number of comments, including other numerical data. From the data, we firstly derive 33 topics with a semi-supervised BERTopic by reflecting article classification information that was not used in previous studies, conducting sentiment analysis of comments on them with a current open-source large language model. We also examine the relationship between the derived topics and personal happiness factors extended to Alderfer's ERG dimension, carrying out additional 3~4-gram keyword frequency analysis, trend analysis, text network analysis based on 3~4-gram keywords, etc. Through this multifaceted approach, we present diverse fresh insights from practical and theoretical perspectives.

Analyzing Different Contexts for Energy Terms through Text Mining of Online Science News Articles (온라인 과학 기사 텍스트 마이닝을 통해 분석한 에너지 용어 사용의 맥락)

  • Oh, Chi Yeong;Kang, Nam-Hwa
    • Journal of Science Education
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    • v.45 no.3
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    • pp.292-303
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    • 2021
  • This study identifies the terms frequently used together with energy in online science news articles and topics of the news reports to find out how the term energy is used in everyday life and to draw implications for science curriculum and instruction about energy. A total of 2,171 online news articles in science category published by 11 major newspaper companies in Korea for one year from March 1, 2018 were selected by using energy as a search term. As a result of natural language processing, a total of 51,224 sentences consisting of 507,901 words were compiled for analysis. Using the R program, term frequency analysis, semantic network analysis, and structural topic modeling were performed. The results show that the terms with exceptionally high frequencies were technology, research, and development, which reflected the characteristics of news articles that report new findings. On the other hand, terms used more than once per two articles were industry-related terms (industry, product, system, production, market) and terms that were sufficiently expected as energy-related terms such as 'electricity' and 'environment.' Meanwhile, 'sun', 'heat', 'temperature', and 'power generation', which are frequently used in energy-related science classes, also appeared as terms belonging to the highest frequency. From a network analysis, two clusters were found including terms related to industry and technology and terms related to basic science and research. From the analysis of terms paired with energy, it was also found that terms related to the use of energy such as 'energy efficiency,' 'energy saving,' and 'energy consumption' were the most frequently used. Out of 16 topics found, four contexts of energy were drawn including 'high-tech industry,' 'industry,' 'basic science,' and 'environment and health.' The results suggest that the introduction of the concept of energy degradation as a starting point for energy classes can be effective. It also shows the need to introduce high-tech industries or the context of environment and health into energy learning.

Full-text databases as a means for resource sharing (자원공유 수단으로서의 전문 데이터베이스)

  • 노진구
    • Journal of Korean Library and Information Science Society
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    • v.24
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    • pp.45-79
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    • 1996
  • Rising publication costs and declining financial resources have resulted in renewed interest among librarians in resource sharing. Although the idea of sharing resources is not new, there is a sense of urgency not seen in the past. Driven by rising publication costs and static and often shrinking budgets, librarians are embracing resource sharing as an idea whose time may finally have come. Resource sharing in electronic environments is creating a shift in the concept of the library as a warehouse of print-based collection to the idea of the library as the point of access to need information. Much of the library's material will be delivered in electronic form, or printed. In this new paradigm libraries can not be expected to su n.0, pport research from their own collections. These changes, along with improved communications, computerization of administrative functions, fax and digital delivery of articles, advancement of data storage technologies, are improving the procedures and means for delivering needed information to library users. In short, for resource sharing to be truly effective and efficient, however, automation and data communication are essential. The possibility of using full-text online databases as a su n.0, pplement to interlibrary loan for document delivery is examined. At this point, this article presents possibility of using full-text online databases as a means to interlibrary loan for document delivery. The findings of the study can be summarized as follows : First, turn-around time and the cost of getting a hard copy of a journal article from online full-text databases was comparable to the other document delivery services. Second, the use of full-text online databases should be considered as a method for promoting interlibrary loan services, as it is more cost-effective and labour saving. Third, for full-text databases to work as a document delivery system the databases must contain as many periodicals as possible and be loaded on as many systems as possible. Forth, to contain many scholarly research journals on full-text databases, we need guidelines to cover electronic document delivery, electronic reserves. Fifth, to be a full full-text database, more advanced information technologies are really needed.

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A Model to Predict Popularity of Internet Posts on Internet Forum Sites (인터넷 토론 게시판의 게시물 인기도 예측 모델)

  • Lee, Yun-Jung;Jung, In-Jun;Woo, Gyun
    • The KIPS Transactions:PartD
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    • v.19D no.1
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    • pp.113-120
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    • 2012
  • Today, Internet users can easily create and share the digital contents with others through various online content sharing services such as YouTube. So, many portal sites are flooded with lots of user created contents (UCC) in various media such as texts and videos. Estimating popularity of UCC is a crucial concern to both users and the site administrators. This paper proposes a method to predict the popularity of Internet articles, a kind of UCC, using the dynamics of the online contents themselves. To analyze the dynamics, we regarded the access counts of Internet posts as the popularity of them and analyzed the variation of the access counts. We derived a model to predict the popularity of a post represented by the time series of access counts, which is based on an exponential function. According to the experimental results, the difference between the actual access counts and the predicted ones is not more than 10 for 20,532 posts, which cover about 90.7% of the test set.

Machine Learning based Firm Value Prediction Model: using Online Firm Reviews (머신러닝 기반의 기업가치 예측 모형: 온라인 기업리뷰를 활용하여)

  • Lee, Hanjun;Shin, Dongwon;Kim, Hee-Eun
    • Journal of Internet Computing and Services
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    • v.22 no.5
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    • pp.79-86
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    • 2021
  • As the usefulness of big data analysis has been drawing attention, many studies in the business research area begin to use big data to predict firm performance. Previous studies mainly rely on data outside of the firm through news articles and social media platforms. The voices within the firm in the form of employee satisfaction or evaluation of the strength and weakness of the firm can potentially affect firm value. However, there is insufficient evidence that online employee reviews are valid to predict firm value because the data is relatively difficult to obtain. To fill this gap, from 2014 to 2019, we employed 97,216 reviews collected by JobPlanet, an online firm review website in Korea, and developed a machine learning-based predictive model. Among the proposed models, the LSTM-based model showed the highest accuracy at 73.2%, and the MAE showed the lowest error at 0.359. We expect that this study can be a useful case in the field of firm value prediction on domestic companies.

A Review of Cross-Cultural Design to Improve User Engagement for Learning Management System

  • Farhan Hanis Muhmad Asri;Dalbir Singh;Zulkefli Mansor;Helmi Norman
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.18 no.2
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    • pp.397-419
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    • 2024
  • Online learning has become a widespread practice for students and teachers in acquiring and delivering knowledge. Education platforms have become prominent in the 21st century with the evolution of technology and the accessibility to online learning. As a result, various learning management systems (LMSs) have been introduced to facilitate online interaction between users. For instance, communication between students and teachers at school. However, there is a need to emphasise user engagement in LMS to enhance the online learning experience amongst students since the design of LMS affects user engagement. This study utilised a systematic literature review (SLR) that examined 74 articles published between 2014 and 2023, focusing on cross-cultural design (CCD), user-centred design (UCD), and usability in LMS design. This study aimed to review CCD and its association with UCD, user interfaces (UI), and user experience (UX) in the context of LMS. CCD has been introduced as an approach to design that embraces different cultures, languages, and social contexts, while UCD plays a significant role in defining user engagement for LMS. All elements in CCD and UCD help create a better user experience for LMS. Besides, this study reviewed the usability of selected LMS to give insights to developers in creating a positive user engagement. An insight into cultural factors that influence the usability of LMS has revealed their value for LMS design, such as the UI/UX elements. Initially, this study may guide future researchers in improving education quality by emphasising CCD and LMS usability, which can enhance user engagement.

Review of Public Health Aspects of Exposure to Agent Orange (고엽제 노출에 따른 건강위해의 보건학적 고찰)

  • Yang, Won-Ho;Hong, Ga-Yeon;Kim, Geun-Bae
    • Journal of Environmental Health Sciences
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    • v.38 no.3
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    • pp.175-183
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    • 2012
  • Objectives: Controversy regarding the relationship between exposure to Agent Orange and disease has progressed for more than four decades, both at home and abroad. Recently, the allegation by US veteran Steve House of the burial of Agent Orange at the US Army base Camp Carroll located in Waegwan-eup, Korea, has emerged. We reviewed published articles and reports related to Agent Orange. Methods: Articles and reports were collected online using the keywords 'agent orange' and 'health' and then reviewed. Results: A number of epidemiologic studies have reported disease outcomes due to exposure to Agent Orange, while others were unable to establish a link to the injuries of veterans of the Vietnam War. This can be explained by the fact that accurate exposure assessment should be carried out since exposure misclassification in epidemiologic studies can affect estimates of risk. In the case of the burial of Agent Orange at Camp Carroll, an exposure pathway could be through underground water supplies, which differs from the cases of Vietnam and Seveso in Italy. Conclusion: There still remains a dispute among academics regarding the relationship between exposure to Agent Orange and disease, although Agent Orange is a highly toxic chemical. This dispute indicates that accurate exposure pathway and exposure assessment is needed.

A Review Study of Researches on Acupuncture Therapy to Pregnant Women (임산부의 침치료에 대한 국내외 연구동향 분석)

  • Ryu, Soo-Hyeong;Park, Kang-In;Kim, Jin-Woo;Park, Kyoung-Sun;Lee, Jin-Moo
    • The Journal of Korean Obstetrics and Gynecology
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    • v.26 no.4
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    • pp.107-122
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    • 2013
  • Objectives: This study was conducted to investigate the effectiveness and safety of acupuncture therapy for pregnant women. Researches on acupuncture therapy for pregnant women published since 2000 until 2013 were selected and analyzed. Methods: Bibliographic search was carried out using several online database systems using keywords like 'pregnancy', 'pregnant', 'acupuncture', 'forbidden points' within a 13-year time span (2000-2013). Results: 18 journal articles published in Korea and 22 journal articles published abroad were selected. It is reported that acupuncture has significant effect on low back pain and pelvic pain, depression, insomnia during pregnancy. Stimulation of acupuncture during pregnancy seems to be safe with respect to obstetric adverse effects. Conclusions: We can conclude that further investigation is needed to accumulate enough information to establish evidence for acupuncture therapy for pregnant women.