• Jounal of The Korea Society of Information Technology Policy & Management
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• v.11 no.6
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• pp.1503-1507
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• 2019

With the softness of online entertainment news articles and the increasing number of quick-reporting articles in the entertainment sector, many people have access to entertainment front-page articles and are now able to make reviews of celebrities. It is not easy to systematically analyze which news articles are about which celebrities in a real-time environment, although their reputation is a key factor in the entertainment agency's business strategy, which should make the most of its affiliated celebrity resources. Based on the amount of celebrity references mentioned in entertainment news data, this paper proposes an entertainment news keyword analysis system, which extracts celebrities that are the subject of the article and associates them with the celebrity entertainment agency in question. Through the system proposed in this paper, advertisers or entertainment agencies can judge the value of the celebrity as reference material for the business. In addition, it can lay the groundwork for an investment strategy by predicting the outlook for the entertainment company for brokerages and investors.

• 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.

• Journal of the Korea Society of Computer and Information
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• v.25 no.7
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• pp.167-173
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• 2020

This study aims to analyze the number and trend of news media news through timely analysis of how the articles about airlines and employees show changes before and after Corona19 in the situation where the world economy faces various problems due to the global pandemic of Corona19. For this purpose, the number of articles and trends related to airlines and employees were analyzed and visualized before and after Corona19 using the Korea Press Foundation Bigkinds news analysis service. For this purpose, the Bigkinds service system was extracted from January 1, 2019 to May 31, 2019 and from January 1, 2020 to May 31, 2020. The results of the analysis showed that the number of articles before and after Corona 19 exploded when aviation related events occurred. And it was confirmed that the trend is changing due to the restructuring news. Government and airlines will need to make active efforts to overcome the crisis in the aviation industry due to the impact of Corona 19. The results of this study are significant in that it analyzed the number and trends related to news articles before and after Corona 19, and suggested practical implications for establishing strategies for the future impacts on airlines and employees.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.847-854
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• 2022

The aim of this study is to develop a Named Entity Recognition (NER) model to automatically identify construction-related organizations from news articles. This study collected news articles using web crawling technique and construction-related organizations were labeled within a total of 1,000 news articles. The Bidirectional Encoder Representations from Transformers (BERT) model was used to recognize clients, constructors, consultants, engineers, and others. As a pilot experiment of this study, the best average F1 score of NER was 0.692. The result of this study is expected to contribute to the establishment of international business strategies by collecting timely information and analyzing it automatically.

• 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.10 no.11
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• pp.329-340
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• 2010

This paper aims to analyze the hyperlink between the portal sites and the press dot coms news and to grasp the features of news service on the online journalism. As a result of the analysis, the portal sites, in the number of news articles which the hyperlink service had been provided, were more than the press dot coms. But in the number of the hyperlinks in the news story which hyperlink service had been provided, the press dot coms were more than the portal sites. The contents that were hyperlinked to the news stories of online journalism were composed of a informative type and an advertising one. All contents that were hyperlinked to the news stories on portal site were informative. On the other hand, about 92% of the contents that were hyperlinked to the news stories on the press web sites were advertising. By means of this analysis, the features of news service on the online journalism could be grasped.

• The Journal of the Korea Contents Association
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• v.22 no.4
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• pp.159-171
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• 2022

This study examined the problem of utilizing celebrity SNS in online news, which have increased by an average of 745 every year since 2010, reaching about 10,000 in 2021. 40 online newspapers were selected and 202,730 news articles produced by these newspapers in July 2021 were analyzed. As a result, 1.27% (2,582) of all articles were found to be using celebrity SNS as a source. This indicates that on average, online newspapers produce 2.08 celebrity SNS-utilized articles per day and 64.7 articles per month. Specifically, entertainer SNS (53.7%) was used the most compared to SNS of politician(39.8%) and influencer(6.5%). Instagram(69.1%, 57.1%) was utilized the most for entertainer and influencer and this were mostly related to personal information. On the other hand, Facebook(70.4%) was cited the most for politician, mostly related to opinions on social/political issues. The average length of SNS-based articles was 536 characters. The problem with news articles utilizing SNS is that most articles simply copy the SNS content without additional coverage(88.4%), and 14% of the articles did not disclose the exact source. Implication of the research on 40 online news agency is discussed.

• Journal of Korea Multimedia Society
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• v.18 no.11
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• pp.1419-1426
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• 2015

Distinguishing border between news and advertising is disappearing. Traditional journalism considered editorial part deals news and ad part handle commercial messages. But now this classification is meaningless. Current news consumers do not separate advertising content and non-advertising content. In Korea, making fake news or paid news pages is becoming social problem. Fake news uses various camouflages to pretend to be real news. This paper descriptively analyzed Korean fake news cases and suggested some guidelines for publishing news. We analyzed 3 major newspaper web sites from July to September, 2014. These three newspapers publish section pages everyday containing fake news or sponsored news. Totally more than one thousand articles were selected for content analysis. We coded the numbers of fake news, day of the week, the rate of sponsored news, average fake news publication number per pages, the conformity between news and advertising, and the type of fake news. We also coded the number of sponsored news article in day sections. We used method of comparing the advertising contents and news articles. As a result, 24.8% of news article were published for the advertising sponsors. Advertorial or fake news were sometimes arranged same pages the same day. We coded the conformity between same advertising and news content. More than 60 percent (60.9%) of fake news match with their sponsors. PR style of fake news is top and advertising type of fake news is the lowest.

• Journal of the Korean Home Economics Association
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• v.45 no.2
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• pp.105-117
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• 2007

The purpose of this study is to examine the producing conventions of lifestyle news and search for problems with these conventions. This research is about the entire process of production of lifestyle news, while dividing it into sourcing conventions and editing conventions. With this concept as a goal, we analyzed the content of lifestyle articles over the last six months in two types of daily papers, and then interviewed journalists in-depth. The results of the study indicate that as for sourcing conventions, reporting is accomplished by focusing on a reporter and using anonymous or false-named news sources. These conventions spread widely over not only ideas but also valuation of news items and security of news sources. This is because in terms of lifestyle news that is closely related to one's private life such as family relations, a reporter often attempts to prevent a news source from being exposed to secondary damage, such as the criticism of readers. In the meantime, editing conventions of lifestyle articles are irrelevant in terms of the quality of each media enterprise. Instead, these conventions are connected with the day of publication. Moreover, editors tend to approach editing conventions to spread the culture of upper classes, recognizing that the readers are consumers who have purchasing power.

• The Journal of Society for e-Business Studies
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• v.21 no.1
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• pp.15-32
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• 2016

Online news on the Internet, as published open data, contain facts or opinions about a specific affair and hence influences considerably on the decisions of the general publics who are interested in a particular issue. Therefore, we can predict the people's choices related with the issue by analyzing a large number of related internet news. This study aims to propose a text analysis methodto predict the outcomes of events that take place in a specific place. We used topics of the news articles because the topics contains more essential text than the news articles. Moreover, when it comes to mobile environment, people tend to rely more on the news topics before clicking into the news articles. We collected the titles of news articles and divided them into the learning and evaluation data set. Morphemes are extracted and their polarity values are identified with the learning data. Then we analyzed the sensitivity of the entire articles. As a result, the prediction success rate was 70.6% and it showed a clear difference with other analytical methods to compare. Derived prediction information will be helpful in determining the expected demand of goods when preparing the event.