• Fashion & Textile Research Journal
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• v.22 no.5
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• pp.551-560
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• 2020

Due to the nature of fashion design that responds quickly and sensitively to changes, accurate forecasting for upcoming fashion trends is an important factor in the performance of fashion product planning. This study analyzed the major phenomena of fashion trends by introducing text mining and a big data analysis method. The research questions were as follows. What is the key term of the 2010SS~2019FW fashion trend? What are the terms that are highly relevant to the key trend term by year? Which terms relevant to the key trend term has shown high frequency in news articles during the same period? Data were collected through the 2010SS~2019FW Pre-Trend data from the leading trend information company in Korea and 45,038 articles searched by "fashion+material" from the News Big Data System. Frequency, correlation coefficient, coefficient of variation and mapping were performed using R-3.5.1. Results showed that the fashion trend information were reflected in the consumer market. The term with the highest frequency in 2010SS~2019FW fashion trend information was material. In trend information, the terms most relevant to material were comfort, compact, look, casual, blend, functional, cotton, processing, metal and functional by year. In the news article, functional, comfort, sports, leather, casual, eco-friendly, classic, padding, culture, and high-quality showed the high frequency. Functional was the only fashion material term derived every year for 10 years. This study helps expand the scope and methods of fashion design research as well as improves the information analysis and forecasting capabilities of the fashion industry.

• Journal of the Korea Society of Computer and Information
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• v.14 no.12
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• pp.97-107
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• 2009

Television News has significant impact on the information analysis of viewers by delivering world news to anonymous individuals everyday. We need to pay more attention to resolution considering the fact that even slight facial expression and the dress of TV anchor can be noticed by viewers in the high definition age, called HD TV, by radical changes in broadcasting situation. As a result, the beauty of expression that lighting technology has is extremely important in the high definition age. In news broadcast, as a phenomenon according to this change in trend, people have been looking for change in order to break with traditional TV news production by adopting DLP(Digital Lighting Processing) or LED(Light Emitting Diode). This effort has contributed to creating proper picture quality appropriate for HD TV. Nowadays Digital imaging is creating new trend in TV news production method from traditional analog-based lighting environment thanks to the development of IT(Information Technology) and digitalized lighting equipment. This change has led to building of HD studio and appropriate sets and lighting system. There are film set and projector which projects image on the screen and PDP, LCD, and DLP which has been used widely in recent years and LED which is often used as background in news program as examples, which has appeared since 1990s with HD TV. In this article, I analyzed the KBS News 9 lnce 1990s with in order to research the influence of television image component on the alyzed the KBS of TV article, I. I wille uggest the category of TV anchor image formulation in delivering information by means of lnce 1990s with based on the analysis result.

• Journal of Preventive Medicine and Public Health
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• v.53 no.2
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• pp.126-134
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• 2020

Objectives: Cancer diagnoses have a tremendous impact on individuals and communities, drawing intense public concern. The objective of the current research was to examine news coverage and content related to cancer-related issues in Korean newspapers. Methods: Primarily using the database system of the Korea Press Foundation, we conducted a content analysis of 2806 articles from 9 Korean daily newspapers during a recent 3-year period from 2015 to 2017. Thematic categories, the types of articles, attitudes and tone, and the number of sources in each article were coded and classified. Results: Many news articles dealt with a diverse range of themes related to cancer, including general healthcare information, the latest research and development, specific medical institutions and personnel, and technology and products, which jointly accounted for 74.8% of all articles. Those thematic categories differed markedly in terms of article type, tone, and the number of cited sources. News articles provided extensive information about healthcare resources, and many articles seemed to contain advertising content. However, the content related to complex social issues such as National Health Insurance did not include enough information for the reader to contextualize the issues properly or present the issues systematically. Conclusions: It can be assumed that the media exert differential influence on individuals through news coverage. Within the present reporting framework, the availability and usefulness of information are likely to depend solely on individuals' capabilities, such as financial and health literacy; this dependency has a negative impact on knowledge gaps and health inequities.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.10
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• pp.4833-4848
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• 2019

This paper introduces the structure and effects of Kakao's news curation algorithm, which is created based on the Deep Reading Index (DRI). The DRI examines the extent of deep reading through content reading time, that is, the duration of reader engagement with an article. Current news curation algorithms focus on reader choice, with the click-through rate or pageviews as the gauge for consumption frequency. DRI is a product of the challenge of introducing and adopting a new factor called 'consumption time' instead of 'frequency of consumption', which is the basis of existing curation algorithms. The analysis of DRI-based services proves that the new algorithm can act as a curation system that is more effective in providing in-depth and quality news reports.

• 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.

• Korea Trade Review
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• v.47 no.2
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• pp.121-132
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• 2022

This study aims to find out the ESG management keywords in the logistics industry through social network analysis using news article and sustainable management reports. In recent years, global climate change and Covid-19 have spurred companies to step up their new management system called ESG management. ESG is a combination of Environment, Social, and Governance. In the past, companies' financial performance was the most important, but in the current investment market, the movement to reflect ESG management factors in investment decisions is strengthening. This study aims to find out degree centrality, betweenness centrality, and closeness centrality through social network analysis after collecting related keywords to derive ESG management issues of logistics companies. This study collected 2,359 news articles searched under the keywords "ESG", "Logistics". In addition, data on ESG activities were also used for analysis by referring to the sustainable management reports of logistics companies. As a result of the analysis of degree centrality, it was found that ESG management of logistics companies is in progress, focusing on small enterprises and eco-friendly keywords, and is concentrated on social responsibility and eco-friendly activities. In the betweenness centrality analysis, logistics companies such as HMM and CJ Logistics were derived in a high ranking. In the closeness centrality analysis, eco-friendly keywords topped the list, while the number of keywords related to governance was relatively small, suggesting that logistics companies need to improve their governance structure.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.2
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• pp.333-336
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• 2020

AI-powered robot news is drawing attention as artificial intelligence technology is fully spread in the news distribution field. Robot news still has many technical and ethical problems, but academic research on this is insufficient. This study analyzes the issue of robot writing in artificial intelligent based robot journalism industry using SWOT analysis. As a result, the advantages of big data processes, accurate information gathering, high efficiency and disadvantages such as lack of independent arguments and lack of evidence and opportunities for technical development, government support, academic development, and industrial applications, and threats such as uncritical acceptance and lack of talent have been found. This study suggests three future-oriented directions, such as human-machine collaboration, intelligent news, and chat-bot, through previous studies on the development direction of robot journalism-based article writing.

• International Journal of Computer Science & Network Security
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• v.24 no.2
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• pp.113-123
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• 2024

Stock market news sentiment analysis (SA) aims to identify the attitudes of the news of the stock on the official platforms toward companies' stocks. It supports making the right decision in investing or analysts' evaluation. However, the research on Arabic SA is limited compared to that on English SA due to the complexity and limited corpora of the Arabic language. This paper develops a model of sentiment classification to predict the polarity of Arabic stock news in microblogs. Also, it aims to extract the reasons which lead to polarity categorization as the main economic causes or aspects based on semantic unity. Therefore, this paper presents an Arabic SA approach based on the logistic regression model and the Bidirectional Encoder Representations from Transformers (BERT) model. The proposed model is used to classify articles as positive, negative, or neutral. It was trained on the basis of data collected from an official Saudi stock market article platform that was later preprocessed and labeled. Moreover, the economic reasons for the articles based on semantic unit, divided into seven economic aspects to highlight the polarity of the articles, were investigated. The supervised BERT model obtained 88% article classification accuracy based on SA, and the unsupervised mean Word2Vec encoder obtained 80% economic-aspect clustering accuracy. Predicting polarity classification on the Arabic stock market news and their economic reasons would provide valuable benefits to the stock SA field.

• Korean Journal of Legislative Studies
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• v.27 no.3
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• pp.155-188
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• 2021

This study examines dynamics in election news making. It is important to understand when and how news media produce election news in order to grasp news making and voting behavior. The news media sometimes make election news by focusing on issues and policies. Often they frame elections as a game and focus on election strategies while covering elections. This article argues that as time goes by during the election period, the number of policy news tends to decrease while the frequency of strategic news is likely to increase. Also, TV's and newspapers show distinctive patterns of election news making. In order to examine the arguments, this study categorizes election news stories into policy and strategic news stories produced during the 2020 Korean congressional elections and constructs daily time-series data of them. The results of structural break and regression analyses partially support the arguments.

• The Journal of Economics, Marketing and Management
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• v.9 no.1
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• pp.1-14
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• 2021

Purpose: The article deals with the proposition that consumers' fashion consumption behavior will still follow the consumption behavior of fast fashion, despite recognizing the importance of slow fashion. Research design, data and methodology: The research model to verify this proposition is topic modelling with big data including unstructured textual data. we combined 5,506 news articles posted on Naver news search platform during the 2003-2019 period about fast fashion and slow fashion, high-frequency words have been derived, and topics have been found using LDA model. Based on these, we examined consumers' perception and consumption behavior on slow fashion through the analysis of Topic Network. Results: (1) Looking at the status of annual article collection, consumers' interest in slow fashion mainly began in 2005 and showed a steady increase up to 2019. (2) Term Frequency analysis showed that the keywords for slow fashion are the lowest, with consumers' consumption patterns continuing around 'brand.' (3) Each topic's weight in articles showed that 'social value' - which includes slow fashion - ranked sixth among the 9 topics, low linkage with other topics. (4) Lastly, 'brand' and 'fashion trend' were key topics, and the topic 'social value' accounted for a low proportion. Conclusion: Slow fashion was not a considerable factor of consumption behavior. Consumption patterns in fashion sector are still dominated by general consumption patterns centered on brands and fast fashion.