• Journal of the Korean Operations Research and Management Science Society
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• v.41 no.2
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• pp.81-100
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• 2016

Much effort has been exerted to analyze online texts and understand how empirical results can help improve sales performance. In this research, we aim to extend this stream of research by decomposing online texts based on text sources, namely, companies and consumers. To be specific, we investigate how online texts driven by companies differ from those generated by consumers, and the extent to which both types of online texts have different effects on online sales. We obtained sales data from one of the biggest game publishers and merged them with online texts provided by companies using news articles and those created by consumers in user communities. The empirical analyses yield the following findings. Word visualization and topic analyses show that firms and consumers generate different contexts. Specifically, companies spread word to promote their own events whereas consumers produce online words to share winning strategies. Moreover, online sales are influenced by consumer-generated community topics whereas firm-driven topics in news articles have little to no effect. These findings suggest that companies should focus more on online texts generated by consumers rather than spreading their own words. Moreover, online sales strategies should take advantage of specific topics that have been proven to increase online sales. In particular, these findings give startup companies and small business owners in variety of industries the advantage when they use the online channel for distribution and as a marketing platform.

• The Journal of the Korea Contents Association
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• v.17 no.3
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• pp.474-485
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• 2017

Sungnyemun Gate, Korea's National Treasure No.1, was destroyed by fire on February 10, 2008 and has been re-opened to the public again as of May 4, 2013 after a reconstruction work. Sungnyemun Gate become a national issue and draw public attention to be a major topic on news or research. In this research, text mining and association rule mining techniques were used on keyword of newspaper articles related to Sungnyemun Gate as a cultural heritage from 2002 to 2016 to find major keywords and keyword association rule. Next, we analyzed some typical and specific keywords that appear frequently and partially depending on before and after the fire and newpaper companies. Through this research, the trends and keywords of newspapers articles related to Sungnyemun Gate could be understood, and this research can be used as fundamental data about Sungnyemun Gate to information producer and consumer.

• The Transactions of the Korea Information Processing Society
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• v.6 no.2
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• pp.282-291
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• 1999

In order to construct the News Video Database System, cut detection technique is very important. In general, the color histogram, $\chi$2 histogram or Bin-to-Bin difference(B2B) techniques are mainly using for the scene partitioning. In this paper, we propose the efficient algorithm that is applied the weight in terms of NTSC standard to cut detection. This algorithm is able to reduce the time of acquiring and comparing histogram using by separate calculation of R, G, and B for the color histogram technique. And it also provide the efficient selection method fo threshold value by and use the news videos of KBS, MBC, SBS, CNN and NHK as experimental domains. By the result of experiment, we present the proposed algorithm is more efficient for cut detection than the previous methods, and that the basis for the automatic selection of threshold values.

• The Journal of the Korea Contents Association
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• v.19 no.6
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• pp.24-32
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• 2019

This study examines the extent to which the differences in perceptions regarding principles of journalism and political identity between journalists and their news organizations are related to journalists' psychological burnout. To understand this, this study analyzes the secondary data of the 2017 South Korean journalists' consciousness conducted by the Korean Press Foundation. Psychological burnout consists of three subdimensions of MBI-GS: cynicism, lack of professional efficacy, and exhaustion. The differences in perceptions regarding the principles of journalism between journalists and their affiliated news organizations is measured by the differences in each of the seven reporting principles. This study found that the larger the difference in the perception of objectivity between journalists and their affiliated news organizations, the more likely they were to experience cynicism, lack of professional efficacy, and exhaustion. The greater the difference in political identity between journalists and their own organization, the more likely they were to have greater cynicism and exhaustion.

• Journal of the Korea Convergence Society
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• v.12 no.7
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• pp.31-36
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• 2021

As the global economy stagnated due to the Corona 19 virus from Wuhan, China, most countries, including the US Federal Reserve System, introduced policies to boost the economy by increasing the amount of money. Most of the stock investors tend to invest only by listening to the recommendations of famous YouTubers or acquaintances without analyzing the financial statements of the company, so there is a high possibility of the loss of stock investments. Therefore, in this research, I have used artificial intelligence deep learning techniques developed under the existing automatic trading conditions to analyze and predict macro-indicators that affect stock prices, giving weights on individual stock price predictions through correlations that affect stock prices. In addition, since stock prices react sensitively to real-time stock market news, a more accurate stock price prediction is made by reflecting the weight to the stock price predicted by artificial intelligence through stock market news text mining, providing stock investors with the basis for deciding to make a proper stock investment.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.579-585
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• 2023

The purpose of this study is to explore keywords within stalking-related news articles according to political orientation through the text network analysis, and then to examine the implicit intentions. Selecting total 1,607 articles including 824 articles of the conservative press(The Chosun Ilbo, The Joongang Ilbo) and 783 articles of the progressive press(The Hankyoreh, The Kyunghyang Shinmun) reported from January 1, 2018 to December 31, 2022, this study explored the aspect of topic category drawn through the topic modeling technique based on LDA(Latent Dirichlet Allocation). In the results of this study, the common topics of the conservative and progressive press were improvement of the perception of gender-based violence, personal protection & intensity of punishment, and disclosure of stalkers' personal information. Regarding the topics differently shown in those two press, the conservative press showed stalkers' harmful act, and outline of 'murder case at Sindang Station' while the progressive press showed request for aggravated punishment on the 'murder case at Sindang Station', and eradication of sexual exploitation crime (in cyber space). The results of this study imply that there are changes in the type of reporting according to ideological opinions about stalking in news articles.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.509-515
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• 2023

Despite the continued development of alternative energies, fuel consumption is increasing. In particular, the price of gasoline fluctuates greatly according to fluctuations in international oil prices. Gas stations adjust their gasoline inventory to respond to gasoline price fluctuations. In this study, news datasets is used to analyze the gasoline consumption patterns through fluctuations of the gasoline inventory. First, collecting news datasets with web crawling. Second, summarizing news datasets using KoBART, which summarizes the Korean text datasets. Finally, preprocessing and deriving the fluctuations factors through N-Gram Language Model and TF-IDF. Through this study, it is possible to analyze and predict gasoline consumption patterns.

• 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 Information Technology Services
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• v.11 no.3
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• pp.39-48
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• 2012

It is essential that firm makes a rational and scientific decision making and creates a news value for the future direction. To do so, many firms attempt to collect meaningful data and find the filtered and refined implication for the better customer relationship and the active market drive through the various analytic tools. Among the possible IT solutions, utilization of 'Big Data' is becoming more attractive and necessary in such a way that it would help firms obtain the systemized and demanding information and facilitate their decision making process to keep up with the market needs. In this paper, it introduces the concepts and development of 'Big Data' recognized as a IT resource and solution under the rapidly changing firm environment. This study also presents the several firm cases using Big Data' and the Oracle's total data management and analytic solutions in order to support the application of 'Big Data'. Finally this paper provides a holistic viewpoint and realistic approach on use of 'Big Data' to create a new value.

• The Transactions of the Korea Information Processing Society
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• v.6 no.5
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• pp.1189-1202
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• 1999

As compared with VOD data, NOD article data has the following characteristics: it is created at any time, has a short life cycle, is selected as not one article but several articles by a user, and has high access locality in time. Because of these intrinsic features, user access patterns of NOD article data are different from those of VOD. Thus, building NOD system using the existing techniques of VOD system leads to poor performance. In this paper, we analysis the log file of a currently running electronic newspaper, show that the popularity distribution of NOD articles is different from Zipf distribution of VOD data, and suggest a new popularity model of NOD article data MS-Zipf(Multi-Selection Zipf) distribution and its approximate solution. Also we present a life cycle model of NOD article data, which shows changes of popularity over time. Using this life cycle model, we develop LLBF (Largest Life-cycle Based Frequency) prefetching algorithm and analysis he performance by simulation. The developed LLBF algorithm supports the similar level in hit-ratio to the other prefetching algorithms such as LRU(Least Recently Used) etc, while decreasing the number of data replacement in article prefetching and reducing the overhead of the prefetching in system performance. Using the accurate user access patterns of NOD article data, we could analysis correctly the performance of NOD server system and develop the efficient policies in the implementation of NOD server system.