• Journal of the Korean Society of Clothing and Textiles
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• v.45 no.2
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• pp.285-304
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• 2021

Today, false news is increasing in volume, and fashion news often circulates uncritically. Therefore, an evaluation framework is needed to determine whether fashion news is accurate or good. In journalism, the judgment of good news is made through the criterion of news value factors. These factors are the criteria for assessing the likelihood of an event being reported in the news. Through the study of news value by various journalistic scholars, this study selected nine news value factors applicable to the value measurement of fashion news as the framework of analysis. Based on this, after analyzing the actual news on online fashion media, new characteristics and content were reconstructed for fashion news. As a result of the study, it was finally selected that the crucial factors were: expertise, social importance, timelessness, conflict, and negativity for measuring the value of fashion news. To assess the news value of fashion accurately, this study found that reconceptualized news values are needed, which are different from the news values of general journalism. The study is meaningful in that it explores elements and content for the development of a theoretical framework for the qualitative evaluation of fashion news.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.12
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• pp.8195-8209
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• 2015

The purpose of this paper is to propose a method for recommendation and personalization of important news articles based on evaluating news value. Evaluation of news is the approach by which editors select news articles for cover-story in traditional offline news papers area. For this, my study proposes a suite of methods to select and personalize a set of news based on evaluating news articles, not just on the personal preference for them. The aforementioned the value of news articles including social impact, novelty, relevance to each audience, and human interest, all of which have been factorized in many previous studies, is a main concept for a procedural and structural application methodology deduced in this study. After a comparative case study with other online news services, it was shown that my research provides more effective way to select important news articles in terms of user satisfaction than others.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.31-42
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• 2024

Today, news avoidance has become an inevitable trend, particularly exacerbated since the outbreak of the COVID-19 pandemic in 2020. To delve deeper into the shifting tendencies of news consumers towards news avoidance and unveil the motivations behind this avoidance, this study recruited 500 Chinese news consumers aged between 20 and 60 years old, employing survey questionnaires as the research method. Through an indepth examination of their news consumption behavior at different stages of the COVID-19 pandemic, we discovered that individuals' risk perceptions and efficacy beliefs significantly influence their patterns of news consumption. Furthermore, we identified negative emotions, information overload, and media distrust as the primary reasons for news avoidance among Chinese news consumers during the COVID-19 crisis. These findings Not only provide crucial insights into understanding the dynamics of news consumption behavior but also offer valuable reference points for the news industry to better fulfill its role and value during crises in the future.

• Journal of Information Processing Systems
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• v.17 no.6
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• pp.1057-1070
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• 2021

Case-related news filtering is crucial in legal text mining and divides news into case-related and case-unrelated categories. Because case-related news originates from various fields and has different writing styles, it is difficult to establish complete filtering rules or keywords for data collection. In addition, the labeled corpus for case-related news is sparse; therefore, to train a high-performance classification model, it is necessary to annotate the corpus. To address this challenge, we propose topic-enhanced positive-unlabeled learning, which selects positive and negative samples guided by topics. Specifically, a topic model based on a variational autoencoder (VAE) is trained to extract topics from unlabeled samples. By using these topics in the iterative process of positive-unlabeled (PU) learning, the accuracy of identifying case-related news can be improved. From the experimental results, it can be observed that the F1 value of our method on the test set is 1.8% higher than that of the PU learning baseline model. In addition, our method is more robust with low initial samples and high iterations, and compared with advanced PU learning baselines such as nnPU and I-PU, we obtain a 1.1% higher F1 value, which indicates that our method can effectively identify case-related news.

• Korean journal of communication and information
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• v.71
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• pp.194-223
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• 2015

This study explores a value chain structure of TV program including news, drama, and comedy. The purpose of this research focused on factor analysis and the relationship among viewer's program selection motivations. This research explores correlation between personal value and viewing motivation. This study was to identify the value structure of respondent on TV program(news, drama, comedy) based on means-end chain theory. The research used structured APT laddering questions and 251 data was analysed. Through such analysis, category difference by stage and relationship difference were identified and hierarchical value map was compared. There are four different value ladders: first is attributes, functional consequences, psychological consequences, and final value. The result shows that on news program the basic function is viewers are want to visual factor and quickly acquire social news and they pursue a value of personal social relationship. Whereas, on drama program, the viewers are reflected by around person, and they selected a program based on closed related person. In addition, the viewers are influenced by program's social nomination, production's brand in drama, and performer's nomination, producer and program prominence on comedy. The program selection is highly correlated on program selection's credibility, vital energetic life, and social relationship. The results shows that there was no significant difference between low involvement group and high involvement group for main category involvement group respondents.

• Journal of Internet Computing and Services
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• v.19 no.2
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• pp.49-56
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• 2018

Internet news consumption is rapidly growing in Korea, and majority of that is being done through Naver, Korea's primary search engine. Naver is also the go-to search engine for smartphone use. This study analyzed 824 most popular news accessed via mobile gears; the news items were selected from Naver's 'Daily Top 10 Stories,' dating from March 2016 to December 2016. The results indicate that entertainment news were the most viewed, while political and social issue news were the most liked and commented by mobile users. With regard to news value, 'prominence' and 'impact' were the two most important factors that influenced a user's news selection process in a mobile environment. The degree of a news' 'prominence' was the most important factor that determined the number of views, while 'impact' was critical to determining "the most commented-upon" and "the most liked" news. The results also indicate that mobile news consumers prefer more dramatic storylines and events that incite public anger or grief, threaten the safety of citizens, or evoke emotional sympathy rather than 'hard news' about such subjects as politics and economics.

• The Journal of Bigdata
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• v.1 no.2
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• pp.79-89
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• 2016

News organizations are looking for a way that can be reused accumulated intellectual property in order to find a new insights. BBC is a worldwide media that continually enhances the value of the news articles by using Linked Data model. Thus, utilizing the Linked Data model, by reusing the stored articles, can significantly improve the value of news articles. In this paper, we conducted a study of Linked Data construction for the healthcare news from a newspaper company. The object names associated with medical description or connected to other published information have been constructed into Linked Open Data service. The results of the study are to systematically organize the news data that were accumulated rashly, and to provide the opportunity to find new insights that could not be found before by connecting to other published information. It may be able to contribute to reused news data. Finally, using SPARQL query language can contribute to interactively searched news data.

• The Journal of the Korea Contents Association
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• v.19 no.12
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• pp.249-258
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• 2019

Changes in media technolgy affect the competitive status of broadcasting networks as news media. The competitive media environment has pushed broadcasting network news programs to find new ways for leveling their qualitative performance up and rating. This study focuses on the empirical relationship between the two key value, news quality in terms of fairness and in-depthness and news ratings. This study is based on the analysis of broadcasting network news texts and individual news item raitngs. Empirical relationship between news quality factors and ratings was proved positive. But the relationship between the length of news item and rating was proved negative.

• Proceedings of the IEEK Conference
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• 2001.06c
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• pp.109-112
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• 2001

This paper proposes an efficient algorithm of extracting anchor blocks for a semantic structure of a news video. We define the FRFD to calculate the frame difference of anchor face position rather than simply uses the general frame difference. Since, The FRFD value is sensitive to existing face in frame, anchor block can be efficiently extracted. In this paper, an algorithm to extract a face position using partial decoded MPEG data is also proposed. In this way a news video can be structured semantically using the extracted anchor blocks.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.127-137
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• 2021

Mainland China area has been a long-term, major trade rival and partner of Taiwan, accounting for more than 40% of Taiwan's total annual trade exports, and so Sino-US trade friction is expected to have a significant impact on Taiwan's economy in the future. This study focuses on major bad news of Sino-US trade frictions and how it generates short-term shocks for Taiwan's equity market and fear sentiment. It further explores the mutual interpretation relationship between price changes such as VIX, Taiwan's stock market index, and the VIX ETF to identify which factors have information leadership as leading indicators. The study period covers 750 trading days from 2017/1/3 to 2020/1/31. This study finds that, when a policy news is announced, the stock market index falls significantly, the change in the trading price (net value) of the VIX ETF rises significantly, and the overprice rate significantly drops, but VIX does not, showing that fear sentiment exists in the Taiwan's market. The net value of the VIX ETF shows an information advantage as a leading indicator. This study suggests that, when the world's two largest economies clash over trade, the impact on Taiwan's equity market is inevitable, and that short-term fear effects will arise.