• Journal of Fashion Business
• /
• v.25 no.2
• /
• pp.80-97
• /
• 2021

In this study, the changes in fashion consumption culture in the post-COVID-19 era were examined through big data analysis. Considering that the Chinese market plays a pivotal role in the global fashion industry, big data was collected in the most famous and professional fashion network in China, LADYMAX.cn. As a result of text mining and social network analysis, three major changes were identified as the emerging fashion consumption culture in the post-COVID-19 era. First, as a trend in new media consumption, COVID-19 disease and the development of digital technology tended to encourage consumers to put more importance on the relationship between bloggers and fans than previously. Second, as a trend in reward consumption, consumers tended to be rewarded for their hard work to relieve and comfort their high stress caused by spending a long time worrying about the prolonged COVID-19 situation. Third, as a trend in home-economy consumption, consumers tended to prefer homewear and sportswear more because they were spending longer times at home as the social distancing period was prolonged.

• Knowledge Management Research
• /
• v.22 no.3
• /
• pp.31-53
• /
• 2021

As a communication channel for individuals, social media is affecting various areas such as business, economy, politics, and society. One of the less-studied areas is the law. Therefore, this study collected various information from social media and analyzed its impacts on the legal decisions, especially the Supreme Court decisions in Korea. This study was conducted by compiling information from Internet news articles and public responses. We found that when the negative reactions from the public got higher, the trial duration until the supreme court making the final decisions became shorter. However, we were not able to find the significant relationship between social media reactions and dismissal of appeal nor annulment. Our study would contribute to the information systems and knowledge management research in a sense that the social analytics is applied to the area of legal decisions, instead of using conventional qualitative study methodology. Our study is also meaningful to the practitioners because that big data analytical business can be applied to the field of law by creating a new database for the emerging legal technology. Finally, law makers can think of a better way to standardize the legal decision process to minimize the reverse effects from social media.

• Information Systems Review
• /
• v.21 no.2
• /
• pp.117-137
• /
• 2019

In the Big Data era, data science has become popular with the production of numerous data in various domains, and the power of data has become a competitive power. There is a growing interest in unstructured data, which accounts for more than 80% of the world's data. Along with the everyday use of social media, most of the unstructured data is in the form of text data and plays an important role in various areas such as marketing, finance, and distribution. However, text mining using social media is difficult to access and difficult to use compared to data mining using numerical data. Thus, this study aims to develop Korean Natural Language Application (KoALA) as an integrated application for easy and handy social media text mining without relying on programming language or high-level hardware or solution. KoALA is a specialized application for social media text mining. It is an integrated application that can analyze both Korean and English. KoALA handles the entire process from data collection to preprocessing, analysis and visualization. This paper describes the process of designing, implementing, and applying KoALA applications using the design science methodology. Lastly, we will discuss practical use of KoALA through a block-chain business case. Through this paper, we hope to popularize social media text mining and utilize it for practical and academic use in various domains.

• Journal of Digital Convergence
• /
• v.12 no.2
• /
• pp.1-10
• /
• 2014

Recently, the value and the status of the digital archives that are built individually in the crossroads of oblivion and memory are due to big data has attracted attention globally is confusing. Video data that contains the cultural memory of the digital archive, such as culture, art, life, society, and social conditions of the time, it is a cultural heritage of national common expressed. Also, it remains a trace of history from the various media just like magazines, books, painting, photography, and film. Digital archive system is one of the best research results of media convergence and it has also a good opportunity to take full advantage of the new opportunities and cultural assets. The collection of infinite information of big data in perspective transient that exist at the same time compatibility of big data, it is trying to dismantle the cultural memory of us. It was asserted that must meet the criteria which can correspond to via the new digital era, will be applied to preserve the traditional media. The current image archive is necessary to accommodate proper two different directions.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.11 no.1
• /
• pp.76-81
• /
• 2018

The Internet of Things (IoT), which is emerging as a future economic growth engine, has been actively introduced in areas close to our daily lives. However, there are still IoT security threats that need to be resolved. In particular, with the spread of smart homes and smart cities, an explosive amount of closed-circuit televisions (CCTVs) have been installed. The Internet protocol (IP) information and even port numbers assigned to CCTVs are open to the public via search engines of web portals or on social media platforms, such as Facebook and Twitter; even with simple tools these pieces of information can be easily hacked. For this reason, a big-data analytics system is needed, capable of supporting quick responses against data, that can potentially contain risk factors to security or illegal websites that may cause social problems, by assisting in analyzing data collected by search engines and social media platforms, frequently utilized by Internet users, as well as data on illegal websites.

• The Journal of the Korea Contents Association
• /
• v.19 no.3
• /
• pp.1-9
• /
• 2019

The purposes of the study are to investigate Koreans' perception about Vietnam by analyzing social big data and to seek changing direction in perception. For the purposes, the texts about Vietnam in Naver Blog and Twitter and the number of search and click for Vietnam in Naver were analyzed by Social Metrics of Daum Soft and Datalab of Naver. The study also analyzed the annual change of their interest in Vietnam based on social media. The results showed that Koreans still remember the Vietnam war, have a positive emotion toward Vietnam, and view Vietnam as a country where we can gain mutual benefit by exchange. The findings also indicated that Koreans perceive Vietnam as a favorite tourist spot regardless of age. Meanwhile, children under 12 showed a different pattern of an annual change in perception. It might be a positive sign that Koreans' interest region toward Vietnam would be diversified because children under 12 would be the central axis of cultural contents.

• Nuclear Engineering and Technology
• /
• v.51 no.2
• /
• pp.626-630
• /
• 2019

After several significant nuclear accidents, public attitudes toward nuclear energy technologies and facilities are considered to be one of the essential factors in the national energy and electricity policy-making process of several nations that employ nuclear energy as their key energy resource. However, it is difficult to explore and capture such an attitude, because the majority of prior studies analyzed public attitudes with a limited number of respondents and fragmentary opinion polls. In order to supplement this point, this study suggests a big data analyzing method with K-LIWC (Korean-Linguistic Inquiry and Word Count), sentiment and query analysis methods, and investigates public attitudes, positive and negative emotional statements about nuclear energy with the collected data sets of well-known social media and network services in Korea over time. Results show that several events and accidents related to nuclear energy have consistent or temporary effects on the attitude and ratios of the statements, depending on the kind of events and accidents. The presented methodology and the use of big data in relation to the energy industry is suggested as it can be helpful in addressing and exploring public attitudes. Based on the results, implications, limitations, and future research areas are presented.

• International Journal of Internet, Broadcasting and Communication
• /
• v.13 no.4
• /
• pp.66-71
• /
• 2021

The purpose of this paper is to identify keywords related to museums, gamification, and visitors, and provide basic data that the museum market can be expanded by using gamification. That used to collect data for blogs, news, cafes, intellectuals, academic information by Naver and Daum which is Web documents in Korea, and Google Web, news, Facebook, Baidu, YouTube, and Twitter for analysis. For the data analysis period, a total of one year of data was selected from April 16, 2020 to April 16, 2021, after Corona. For data collection and analysis, the frequency and matrix of keywords were extracted through Textom, a social matrix site, and the relationship and connection centrality between keywords were analysed and visualized using the Netdraw function in the UCINET6 program. In addition, We performed CONCOR analysis to derive clusters for similar keywords. As a result, a total of 25,761 cases that analysing the keywords of museum, gamification and visitors were derived. This shows that the museum, gamification, and spectators are related to each other. Furthermore, if a system using gamification is developed for museums, the museum market can be developed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2018.05a
• /
• pp.103-104
• /
• 2018

Recently, interest in data analysis has increased as the importance of big data becomes more important. Particularly, as social media data and academic research communities become more active and important, analysis becomes more important. In this study, co-word analysis was conducted through altmetrics articles collected from 2012 to 2017. In this way, the co-occurrence network map is derived from the keyword and the emphasized keyword is extracted.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2018.05a
• /
• pp.424-425
• /
• 2018

Recently, interest in data analysis has increased as the importance of big data becomes more important. Particularly, as social media data and academic research communities become more active and important, analysis becomes more important. In this study, co-word analysis was conducted through altmetrics articles collected from 2012 to 2017. In this way, the co-occurrence network map is derived from the keyword and the emphasized keyword is extracted.