• Journal of the Korean Society for Library and Information Science
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• v.53 no.2
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• pp.159-178
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• 2019

The purpose of the study is to examine the trend in the change of relation between countries (Czech and Korea) through analysis of portal new articles. In order to achieve the purpose, we analyzed news articles about Czech from 1990 to March 31st, 2019. We divided it into 6 periods by every 5 years, reviewed 200 news articles for each period totaling 1,200 news articles, and categorized them into 4 categories by subject (politics, economy, society and culture, and educations). The result of the study showed the subject of society and culture represented the largest proportion of all news articles. We also found that the range of changes in the sub-categories of society and culture occurred most extensively. We concluded the paper with several suggestions that could promote cooperation between Korea and Czech.

• Journal of KIISE:Databases
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• v.37 no.3
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• pp.127-136
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• 2010

With rapid growth of information and computer communication technologies, the numbers of digital documents including multimedia data have been recently exploded. In particular, news video database and news video mining have became the subject of extensive research, to develop effective and efficient tools for manipulation and analysis of news videos, because of their information richness. However, many research focus on browsing, retrieval and summarization of news videos. Up to date, it is a relatively early state to discover and to analyse the plentiful latent semantic knowledge from news videos. In this paper, we propose the news video mining system based on multi-modal approach and text mining, which uses the visual-textual information of news video clips and their scripts. The proposed system systematically constructs a taxonomy of news video stories in automatic manner with hierarchical clustering algorithm which is one of text mining methods. Then, it multilaterally analyzes the topics of news video stories by means of time-cluster trend graph, weighted cluster growth index, and network analysis. To clarify the validity of our approach, we analyzed the news videos on "The Second Summit of South and North Korea in 2007".

• Journal of Sport and Applied Science
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• v.8 no.1
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• pp.11-17
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• 2024

Purpose: The purpose of the study was to understand a trend of esports in terms of gamers' and fans' perceptions toward esports using social big data. Research design, data, and methodology: In this study, researchers first selected keywords related to esports. Then a total of 10,138 buzz data created at twitter, Facebook, news media, blogs, café and community between November 10, 2022 and November 19, 2023 were collected and analyzed with 'Textom', a big data solution. Results: The results of this study were as follows. Firstly, the news data's main articles were about competitions hosted by local governments and policies to revitalize the gaming industry. Secondly, As a result of esports analysis using Textom, there was a lot of interest in the adoption of the Hangzhou Asian Games as an official event and various esports competitions. As a result of the sentiment analysis, the positive content was related to the development potential of the esports industry, and the negative content was a discussion about the fundamental problem of whether esports is truly a sport. Thirdly, As a result of analyzing social big data on esports and the Olympics, there was hope that it would be adopted as an official event in the Olympics due to its adoption as an official event in the Hangzhou Asian Games. Conclusions: There was a positive opinion that the adoption of esports as an official Olympic event had positive content that could improve the quality of the game, and a negative opinion that games with actions that violate the Olympic spirit, such as murder and assault, should not be adopted as an official Olympic event. Further implications were discussed.

• Journal of Korea Technology Innovation Society
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• v.19 no.1
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• pp.80-104
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• 2016

Existing methodologies of technology planning about promising new technology focused on target technology itself, so it is true that socio-environmental context which the relevant technology has influence on is not well understood. In this respect, this study is aimed to questingly examine that news content analysis methodologies widely available in the field of science communication can be applied as a complementary methodology for contextual understanding of socio-environment in terms of technology planning about promising new technology. In the co-evolutionary environment of technology-society, promising new technology shows hype phenomenon regarding the relation with the society. Based on this, this study performed news content analysis and examined if the consequences of analysis would match hype cycle. It tried to explore substantive content understanding by socio-environment factors according to specific news frame content. To do this, new content analysis was performed targeting cloud computing as a representative promising new technology. The result of news content analysis targeting general newspapers, business news, IT special newspapers revealed that the tendency of news reporting matched the trend of hype cycle. Particularly, it was verified that reporting attitude and news frame analysis provided useful information to understand contextual content depending on social, economic, and cultural environment factors about promising new technology. The results of this study implied that news content analysis could overcome the limitation of technology information analysis focusing on academic journal patent usually applied for technology planning and could be used as a complementary methodology for understanding the context depending on macro-environment factors. In conclusion, application of news content analysis on the phase of macro-environment analysis of technology planning could contribute to the securement of mutually balanced view in the co-evolutionary perspective of technology-society.

• The Journal of the Korea Contents Association
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• v.22 no.4
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• pp.337-351
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• 2022

With the full spread and rapid development of social media, the trend of decentralization of social media information propagation is becoming clearer day by day, and the segmentation of time by audiences using social media information is clearly progressing. Therefore, this study aims to study the influence relationship between social media attitudes toward fake news, social capital, risk perception, and discriminant intentions based on existing studies. Accordingly, the research model presented related research questions and organized a questionnaire to collect a total of 500 valid surveys. The SPSS 26.0 program and the AMOS 24.0 program were used to analyze the data. The research results are as follows. First, the more positive the user's attitude towards the fake news identification intention of social media, the more they want to use various methods or tools to identify the authenticity of online information. Second, the more positive the user's attitude towards social media fake news, the more aware of the potential threats social media fake news poses to their own physical, psychological, financial and so on. At the same time, by raising one's own awareness of the dangers, counterintelligence intentions against fake news on social media will also increase. Third, the richer the social capital the user has, the stronger the information literacy, and therefore the stronger the identification intention of social media fake news. Fourth, the higher the value of social capital Chinese users have, the greater the damage they have suffered from fake news, and the higher the risk awareness of fake news to protect their interests. Fifth, it means that Chinese users recognized information suspected of social media and took corresponding measures.

• Journal of Korea Multimedia Society
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• v.10 no.8
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• pp.1017-1028
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• 2007

In this paper we propose an effective method to represent, store, and retrieve video streams efficiently from a video database. We extract features from each video frame, normalize the feature values, and represent them as values in the range [0,1]. In this way a video frame with f features can be represented by a point in the f-dimensional space $[0,1]^f$, and thus the video stream is represented by a trail of points in the multidimensional space. The video stream is partitioned into video segments based on camera shots, each of which is represented by a trend vector which encapsulates the moving trend of points in a segment. The video stream query is processed depending on the comparison of those trend vectors. We examine our method using a collection of video streams that are composed of sports, news, documentary, and educational videos. Experimental results show that our trend vector representation reduces a reconstruction error remarkably (average 37%) and the retrieval using a trend vector achieves the high precision (average 2.1 times) while maintaining the similar response time and recall rate as existing methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.12
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• pp.1589-1595
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• 2018

The purpose of this research is to search for and identify trends in adolescent problems on internet news sites. Among the domestic internet news sites, 8,110 articles on adolescent problems from 1993 to 2018 were analyzed for the top three top-ranked 'The Chosunilbo', 'The Dong-A Ilbo', and 'Korea Joongang Daily' news sites. As a result of this study, we have been able to understand the topic of adolescent problems in internet news sites for the last 26 years and find out that the trend of articles has been changed considering the environment, policies and culture related to adolescent problems. This study is meaningful to start from the method to examine the social trends of existing adolescent problems, to expand the scope of adolescent problems and counseling, to use quantitative analysis methods and to provide new information to consider diversity.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.5
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• pp.492-501
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• 2019

To use the system safely in cyberspace, you need to use a security solution that is appropriate for your situation. In order to strengthen cyber security, it is necessary to accurately understand the flow of security from past to present and to prepare for various future threats. In this study, information security words of security/hacking news of Naver News which is reliable by using text mining were collected and analyzed. First, we checked the number of security news articles for the past seven years and analyzed the trends. Second, after confirming the security/hacking word rankings, we identified major concerns each year. Third, we analyzed the word of each security solution to see which security group is interested. Fourth, after separating the title and the body of the security news, security related words were extracted and analyzed. The fifth confirms trends and trends by detailed security solutions. Lastly, annual revenue and security word frequencies were analyzed. Through this big data news analysis, we will conduct an overall awareness survey on security solutions and analyze many unstructured data to analyze current market trends and provide information that can predict the future.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.543-546
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• 2017

Recently, people are using the data analysis in order to follow the new trend in information and communication technology. Media plays an important role to expand the new issue in our society, especially affected to establish social awareness about science and technology. So, We find some major technologies (Machine Learning & Blockchains) of future communication and information based on the 200 news articles through two data analysis methods such as keyword analysis and sentiment analysis. We look forward this paper to constantly develop the technology of information and communication as the guiding frame of the new scientific world.

• Journal of Information Technology Services
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• v.20 no.2
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• pp.77-90
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• 2021

Online and mobile games represent digital entertainment. Not only the game grows fast, but also it has been noted for unique business models such as a subscription revenue model and free-to-play with partial payment. But, a recent revenue mechanism, called a loot-box system, has been criticized due to overspending, weak protection to teenagers, and more over gambling-like features. Policy makers and research communities have counted on expert opinions, review boards, and temporal survey studies to build countermeasures to minimize negative effects of online and mobile games. In this process, speed was not seriously considered. In this study, we attempt to use a big data source to find a way of observing a trend for policy makers and researchers. Specifically, we tried to apply the Word2Vec data mining algorithm to news repositories. From the findings, we acknowledged that the suggested design would be effective in lightening issues timely and precisely. This study contributes to digital entertainment service communities by providing a practical method to follow up trends; thus, helping practitioners have concrete grounds for balancing public concerns and business purposes.