• Korean Educational Research Journal
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• v.43 no.1
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• pp.1-27
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• 2022

As the COVID-19 virus became prevalent worldwide, non-face-to-face contact was implemented in various ways, and the education system also began to draw much attention due to rapid non-face-to-face contact. The purpose of this study is to analyze the direction of non-face-to-face education in line with the continuously changing educational environment to date. In this study, data were visualized using Textom and Ucinet6 analysis tool programs to collect social network big data with various opinions. As a result of the study, keywords related to "COVID-19" were dominant, and keywords with high frequency such as "article" and "news" existed. As a result of the analysis, various issues related to non-face-to-face education, such as network failures and security issues, were identified. After the analysis, the direction of the non-face-to-face education system was studied according to the growth of the education market and changes in the educational environment. In addition, there is a need to strengthen security and feedback on teaching methods in non-face-to-face education analyzed using big data.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.353-360
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• 2023

This paper explores notable shifts in the restaurant startup market following the lifting of social distancing measures. Key trends identified include an escalated interest in startups, a heightened focus on the quality and diversity of food, a relative decline in the importance of delivery services, and a growing interest in specific industry sectors. The study's data collection spanned three years, from April 2021 to May 2023, encompassing the period before and after social distancing. Data were sourced from a range of online platforms, including blogs, news sites, cafes, web documents, and intellectual forums, provided by Naver, Daum, and Google. From this collected data, the top 50 words were identified through a refinement process. The analysis was structured around the social distancing application period, comparing data from April 2021 to April 2022 with data from May 2022 to May 2023. These observed trend changes provide founders with valuable insights to seize new market opportunities and formulate effective startup strategies. In summary, We offer crucial insights for founders, enabling them to comprehend the evolving dynamics in food service startups and to adapt their strategies to the current market environment.

• International Journal of Internet, Broadcasting and Communication
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• v.11 no.2
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• pp.59-66
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• 2019

The emergence of new IT technologies and convergence industries, such as artificial intelligence, bigdata and the Internet of Things, is another chance for South Korea, which has established itself as one of the world's top IT powerhouses. On the other hand, however, privacy concerns that may arise in the process of using such technologies raise the task of harmonizing the development of new industries and the protection of personal information at the same time. In response, the government clearly presented the criteria for deidentifiable measures of personal information and the scope of use of deidentifiable information needed to ensure that bigdata can be safely utilized within the framework of the current Personal Information Protection Act. It strives to promote corporate investment and industrial development by removing them and to ensure that the protection of the people's personal information and human rights is not neglected. This study discusses the strategy of deidentifying personal information protection based on the analysis of fake news. Using the strategies derived from this study, it is assumed that deidentification information that is appropriate for deidentification measures is not personal information and can therefore be used for analysis of big data. By doing so, deidentification information can be safely utilized and managed through administrative and technical safeguards to prevent re-identification, considering the possibility of re-identification due to technology development and data growth.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.11
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• pp.521-526
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• 2017

Data format of Big data is diverse and vast, and its generation speed is very fast, requiring new management and analysis methods, not traditional data processing methods. Textual mining techniques can be used to extract useful information from unstructured text written in human language in online documents on social networks. Identifying trends in the message of politics, economy, and culture left behind in social media is a factor in understanding what topics they are interested in. In this study, text mining was performed on online news related to a given keyword using topic - oriented analysis technique. We use Latent Dirichiet Allocation (LDA) to extract information from web documents and analyze which subjects are interested in a given keyword, and which topics are related to which core values are related.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.332-341
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• 2023

Notable trends in the restaurant start-up market after the lifting of social distancing include increasing interest in start-ups, emphasizing the importance of food quality and diversity, decreasing the relative importance of delivery services, and increasing interest in certain industries. The data collection period is three years from April 2021 to May 2023, including before and after social distancing, and texts extracted from blogs, news, cafes, web documents, and intellectuals provided by Naver, Daum, and Google were collected. For the collected data, the top 30 words were derived through a refining process. In addition, based on April 2021, the application period of social distancing, data from April 2021 to April 2022, and data from May 2022 to May 2023, Through these changes in trends, founders can capture new opportunities in the market and develop start-up strategies. In conclusion, this paper provides important insights for founders in accurately understanding the changes in food service start-up trends and in developing strategies appropriate to the current market situation.

• Journal of Information Technology Services
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• v.14 no.2
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• pp.159-176
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• 2015

As a public medium and one of the big data sources that is accumulated informally and real time, online news comments or replies are considered a significant resource to understand mentalities of article readers. The comments are also being regarded as an important medium of WOM (Word of Mouse) about products, services or the enterprises. If the diffusing effect of the comments is referred to as the degrees of agreement and disagreement from an angle of WOM, figuring out which characteristics of the comments would influence the agreements or the disagreements to the comments in very early stage would be very worthwhile to establish a comment-based eWOM (electronic WOM) strategy. However, investigating the effects of the characteristics of the comments on eWOM effect has been rarely studied. According to this angle, this study aims to conduct an empirical analysis which understands the characteristics of comments that affect the numbers of agreement and disagreement, as eWOM performance, to particular news articles which address a specific product, service or enterprise per se. While extant literature has focused on the quantitative attributes of the comments which are collected by manually, this paper used text mining techniques to acquire the qualitative attributes of the comments in an automatic and cost effective manner.

• Journal of Korea Water Resources Association
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• v.55 no.spc1
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• pp.1235-1249
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• 2022

This study applied the web crawling technique for extracting big data news on water quality accidents in the water supply system and presented the algorithm in a procedural way to obtain accurate water quality accident news. In addition, in the case of a large-scale water quality accident, development patterns such as accident recognition, accident spread, accident response, and accident resolution appear according to the occurrence of an accident. That is, the analysis of the development of water quality accidents through key keywords and sentiment analysis for each stage was carried out in detail based on case studies, and the meanings were analyzed and derived. The proposed methodology was applied to the larval accident period of Incheon Metropolitan City in 2020 and analyzed. As a result, in a situation where the disclosure of information that directly affects consumers, such as water quality accidents, is restricted, the tone of news articles and media reports about water quality accidents with long-term damage in the event of an accident and the degree of consumer pride clearly change over time. could check This suggests the need to prepare consumer-centered policies to increase consumer positivity, although rapid restoration of facilities is very important for the development of water quality accidents from the supplier's point of view.

• Journal of Industrial Convergence
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• v.19 no.3
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• pp.35-40
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• 2021

This study attempted to derive important factors of emerging infectious diseases by collecting and analyzing text data onto emerging infectious diseases. For this purpose, articles in the Naver News database were directly crawled, pre-processed, and used for data analysis. In addition, additional analysis was performed using Big Kinds. As a result of the priority analysis, the importance was shown in the order of corona, infectious disease, quarantine, vaccine, outbreak, virus, infection, and development. As a result of the proximity centrality analysis, the importance was shown in the order of government, death, and plan, and the analysis result of Big Kinds showed that Covid-19 and the Korea Centers for Disease Control and Prevention were important. Based on the results of this study, it can be said that the government's policy support is needed to raise public awareness of new infectious diseases, prevent disease, and develop vaccines and treatments.

• Human Ecology Research
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• v.61 no.4
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• pp.687-707
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• 2023

This study was conducted to obtain useful information on the development of the future second-hand fashion market by obtaining information on the current situation through unstructured text data distributed as news articles related to 'purchase of second-hand clothing' and 'purchase of second-hand luxury goods'. Text-based unstructured data was collected on a daily basis from Naver news from January 1st to December 31st, 2022, using 'purchase of second-hand clothing' and 'purchase of second-hand luxury goods' as collection keywords. This was analyzed using text mining, and the results are as follows. First, looking at the frequency, the collection data related to the purchase of second-hand luxury goods almost quadrupled compared to the data related to the purchase of second-hand clothing, indicating that the purchase of second-hand luxury goods is receiving more social attention. Second, there were common words between the data obtained by the two collection keywords, but they had different words. Regarding second-hand clothing, words related to donations, sharing, and compensation sales were mainly mentioned, indicating that the purchase of second-hand clothing tends to be recognized as an eco-friendly transaction. In second-hand luxury goods, resale and genuine controversy related to the transaction of second-hand luxury goods, second-hand trading platforms, and luxury brands were frequently mentioned. Third, as a result of clustering, data related to the purchase of second-hand clothing were divided into five groups, and data related to the purchase of second-hand luxury goods were divided into six groups.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.139-146
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• 2022

Recently, solving industrial and social problems and creating new values based on big data and AI is being discussed as the main policy goal. The new government also set the digital platform government as a national task in order to achieve new value creation based on big data and AI. However, studies that summarize and diagnose discussions over the past five years are insufficient. Therefore, this study diagnoses the discussions over the past 5 years using the 4th industrial revolution as a keyword. After collecting news editorials from 2017 to 2022 by applying the text mining technique, 9 major topics were discovered. In conclusion, this study provided implications for the government's task to prepare for the future society.