• Journal of Internet Computing and Services
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• v.19 no.4
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• pp.123-133
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• 2018

This paper examined how the millennial generation consumes mobile news through social networking sites with regards to user patterns, preference topics and news values, and whether news topics and news values may influence their overall mobile SNS news consumption and interactivity. The findings show that more than 2/3 of respondents consumed mobile SNS news at least once everyday for 30minutes to one-hour. Male millennials tended to use Facebook and Kakao-talk more than female. While the portal site was the most accessed channel for consuming mobile news, SNS was the second, more than the combined use of national daily papers, TV, and internet newspapers. The respondents' demographic characteristics and news topics also affect the form and degree of news interactivity. With regards to their preferences and prioritization of news values, millennials tend to perceive 'impact' and 'usefulness' as being most important, despite the differences of their demographic characteristics. They also preferred those news values most. There were significant differences in terms of preferred news topics according to the demographics' characteristics.

• Journal of the HCI Society of Korea
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• v.9 no.2
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• pp.5-12
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• 2014

There was widespread criticism of the online news services due to their bias toward sensational and soft news. Thus, news services based on journalist values are socially requested. News source network analysis(NSNA), an algorithm to cluster and weight news sources, quotes, and articles, is suggested as a method to emphasize on journalist values like facts, variety, depth, and criticism in the previous study. This study suggests 'News Sources' as a visualization tool of NSNA. 'News Sources' shows news as bar graphs, weighted by facts and criticism, and arranged by organizations and subjects. This study designed a beta version using KINDS, a news archive of Korean Press Foundation.

• 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 Internet Computing and Services
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• v.18 no.2
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• pp.105-111
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• 2017

This paper explores the characteristics of curated news content. With content analysis of 1020 news clips, the study found that news values immersed in card news differed from those of traditional news. Specifically, timeliness was not regarded as a key factor in newsworthiness. Rather, information and social impacts were highly emphasized. Considering news consumers depend on traditional news for timely news, curated news content was not a replacement for traditional news but a supplement. By refurbishing photos from previous news reports and googling the web for related information, curated news reiterates social meaning and provides relevant information. Furthermore, salience of human interest can be explained by entertaining characteristics of curated news. In story forms, the list technique has several important points to stress, and was more frequently used than inverted pyramids. Another key finding of this study is man-on-the street as the most quoted main sources in the curatorial context.

• 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.

• Korean journal of communication and information
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• v.39
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• pp.324-354
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• 2007

Facts, which constitute news, are as free as air. When they are transformed into news via labor and capital investment of a news organization, the news is deemed to have property values, and the media can claim exclusive rights over the news. The copyright law protects the originality of a work, the uniqueness of reporter's analysis, the selection of words, the arrangement of materials, and the emphasis given on particular points. The name of the game of copyright infringement lies in the infringement of the similarity of the method of expression, not the infringement of the subject. Even though news articles convey information by specifying factual elements of an event or accident, they still have some originality. The judgement that news articles lack of originality is inconsistent with the purpose of the copyright law. Therefore, the law should be amended to articulate that the unauthorized use of news articles without a proper citation shall be the subject of legal action, and courts should decide related cases accordingly.

• Journal of Information Technology Applications and Management
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• v.25 no.1
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• pp.19-32
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• 2018

Fake news is defined as the news articles that are intentionally and verifiably false, and could mislead readers. Spread of fake news may provoke anxiety, chaos, fear, or irrational decisions of the public. Thus, detecting fake news and preventing its spread has become very important issue in our society. However, due to the huge amount of fake news produced every day, it is almost impossible to identify it by a human. Under this context, researchers have tried to develop automated fake news detection method using Artificial Intelligence techniques over the past years. But, unfortunately, there have been no prior studies proposed an automated fake news detection method for Korean news. In this study, we aim to detect Korean fake news using text mining and machine learning techniques. Our proposed method consists of two steps. In the first step, the news contents to be analyzed is convert to quantified values using various text mining techniques (Topic Modeling, TF-IDF, and so on). After that, in step 2, classifiers are trained using the values produced in step 1. As the classifiers, machine learning techniques such as multiple discriminant analysis, case based reasoning, artificial neural networks, and support vector machine can be applied. To validate the effectiveness of the proposed method, we collected 200 Korean news from Seoul National University's FactCheck (http://factcheck.snu.ac.kr). which provides with detailed analysis reports from about 20 media outlets and links to source documents for each case. Using this dataset, we will identify which text features are important as well as which classifiers are effective in detecting Korean fake news.

• 한국IT서비스학회:학술대회논문집
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• 2007.11a
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• pp.641-645
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• 2007

News contents, produced for paper readers, are more and more being used online instead of offline. Internet sites, expecially portals(naver, daum, nate etc.) are dominant marketplaces, where news are exchanged and values are added. So, establishing a new online news service system, which can satisfy news provider(copyright owner) and internet service provider together, is a necessary task under current online-dominant news service environment. UCI(Universal & Ubiquitous Content Identifier) and IPTC NewsML(News Mark-up Language) are considered as useful standards to compromise protection of news-copyright and enhancement of online use of news contents. This study is based on a real case of 'NewsBank' in korea, We expect that this study can show an inspiration to obtain two contradictory goals of copyright protection and free online use of copyright.

• The Transactions of the Korea Information Processing Society
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• v.13 no.5
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• pp.209-216
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• 2024

Real estate market prices are determined by various factors, including macroeconomic variables, as well as the influence of a variety of unstructured text data such as news articles and social media. News articles are a crucial factor in predicting real estate transaction prices as they reflect the economic sentiment of the public. This study utilizes sentiment analysis on news articles to generate a News Sentiment Index score, which is then seamlessly integrated into a real estate price prediction model. To calculate the sentiment index, the content of the articles is first summarized. Then, using AI, the summaries are categorized into positive, negative, and neutral sentiments, and a total score is calculated. This score is then applied to the real estate price prediction model. The models used for real estate price prediction include the Multi-head attention LSTM model and the Vector Auto Regression model. The LSTM prediction model, without applying the News Sentiment Index (NSI), showed Root Mean Square Error (RMSE) values of 0.60, 0.872, and 1.117 for the 1-month, 2-month, and 3-month forecasts, respectively. With the NSI applied, the RMSE values were reduced to 0.40, 0.724, and 1.03 for the same forecast periods. Similarly, the VAR prediction model without the NSI showed RMSE values of 1.6484, 0.6254, and 0.9220 for the 1-month, 2-month, and 3-month forecasts, respectively, while applying the NSI led to RMSE values of 1.1315, 0.3413, and 1.6227 for these periods. These results demonstrate the effectiveness of the proposed model in predicting apartment transaction price index and its ability to forecast real estate market price fluctuations that reflect socio-economic trends.

• The Journal of the Korea Contents Association
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• v.21 no.3
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• pp.10-22
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• 2021

This study conducted usability test to users in 20s in order to find problems for improving news apps of the major broadcasting companies. Efficiency, effectiveness, and satisfaction were evaluated by mobile news content type. Also there is including analysis of the news topics (hard news, soft news) and broadcasters (MBC, SBS). As a result, same problems were found in common items according to mobile news content types. And in the news topic, there was a difference in the news values and news attributes that need to be improved. This study gives practical implications to the news producers to improve the contents of news apps.