• The Journal of the Korea Contents Association
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• v.22 no.1
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• pp.74-85
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• 2022

Along with the change in the values of marriage and the prevalence of non-marriage in Korean society, a new form of family composition called unmarried birth or non-maritalism childbirth has appeared, and social discussion in taking place in connection with the problem of a decrease in the birthrate. Using sentiment analysis and social network analysis, this research explored how the people's sentiment and perception has changed toward 'nonmarital birth.' The data used is comments on news articles from the period of November 2020 to August 2021. As a result of the study, there were a lot of positive comments during the social issue period by marriage, whereas there were many negative comments from the policy agenda to the policy making period. As a result of co-occurrence network analysis, the topic of family norm, policy, and personal aspect appeared. This study is significant in that it revealed that negative perceptions prevailed during the policy-making process after the issue of unmarried births after the issue of unmarried births, and it became a cornerstone of social discussion on unmarried births

• The Journal of the Korea Contents Association
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• v.21 no.11
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• pp.20-29
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• 2021

This study aims to explore the issue of drones and crime in newspaper articles. BIG KINDS, an online news archive of the Korea Press Foundation, collected 1,213 newspaper articles that met the terms of "drone" and "crime" in 11 central and 28 regional comprehensive newspapers between January 1, 1990 and May 1, 2021. Among them, we perform keyword frequency, centrality analysis, network structure construction, CONCOR analysis, and density matrix analysis on 117 key keywords. According to the analysis, the main issues were classified into eight, and the report analysis on drones and crimes in newspaper articles showed that the government's policy-making and social problems on protecting people's privacy, preventing illegal filming, securing navigation safety, social security and resolution. This study attempts to expand the field of humanities and social studies related to drones and crime, and specifically suggests the current status and counterplan against drone-related crimes as policy implications and media implications.

• International Journal of Computer Science & Network Security
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• v.24 no.6
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• pp.216-222
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• 2024

Objectives: To compare the levels of anxiety on GAD-7 scale among undergraduates of dental, medical and engineering students during COVID-19. The secondary objectives were to correlate the factors influencing level of anxiety and to assess the coping strategies practiced by undergraduates' students of Karachi duri.ng COVID-19 outbreak. Methodology: The cross-sectional based survey was conducted online among the medical, dental and engineering undergraduates' university students of private sector in Karachi through purposive sampling technique during COVID-19 lock down period. The GAD-7 validated tool was used along with the demographic variables, related stress factors and the coping skills practiced during this outbreak. Total 571 questionnaires were found completed in all sections. The data was analyzed on SPSS version 23. P-value <0.05 was considered as statistically significant. Results: The mental health of the students was assessed on GADS-7 scale as normal, mild, moderate and severe levels. From the total (n=18-3.2%) were normal, (n=132-23.1%) had mild, (n=343-60.1%) had moderate and (n=78-13.7%) had severe anxiety level on GADS-7. The levels of anxiety on GAD-7 scale were all positively associated with the related stressors at p-value of 0.000. Moreover the results depicted that there was a moderate and positive correlation found (0.456, 0.447, 0.512 and 0.452) for all related stressors and GAD-7 scale. Taking breaks from watching, reading news regarding the outbreak of COVID-19, meditation and engaging in some other activities were the most frequently used coping strategies for all levels of anxiety among three cohorts of undergraduates'. Conclusion: Undergraduates has shown 96.9% drastically increased level of anxiety during the outbreak of COVID 19 pandemic. Taking breaks from watching, reading news regarding the outbreak of COVID-19 was the most frequent behavior practiced by the students.

• The Journal of the Korea Contents Association
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• v.5 no.4
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• pp.237-244
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• 2005

Currently most Internet documents including news data are made based on predefined templates, but templates are usually formed only for main data and are not helpful for information retrieval against indexes, advertisements, header data etc. Templates in such forms are not appropriate when Internet documents are used as data for information retrieval. In order to process Internet documents in various areas of information retrieval, it is necessary to detect additional information such as advertisements and page indexes. Thus this study proposes a method of detecting the layout of web pages by identifying the characteristics and structure of block tags that affect the layout of web pages and calculating distances between web pages. As a result of experiment, we can successfully extract 640 documents from 1000 samples and obtain 64% recall rate. This method is purposed to reduce the cost of web document automatic processing and improve its efficiency through applying the method to document preprocessing of information retrieval such as data extraction and document summarization.

• Journal of the Korean Society for Marine Environment & Energy
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• v.20 no.2
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• pp.117-125
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• 2017

SNS Big-data Analysis means to find potential value from big data which has produced by the social media. In this paper, SNS Big-data has been analysed to find Korean concerns by using 24 key words from the marine and fisheries sector. Among 24 key words, seafood, shipping and Dokdo Island are the most mentioned ones. Some key words such as ocean policies and marine security that have less concerns have bess mentioned less. Also, key words that are led by government are mostly mentioned by news media, but key words that are led by private sector and have intimate relationship with people's lives are mostly mentioned by Blogs and Twitters. Therefore, reflecting close national concerns by SNS Big-data Analysis and especially resolving negative factors are the most significant part of the policy establishment. Also, differentiated promotion methods need to be prepared because the frequency of key words mentioned from each type of media are different.

• The Journal of the Korea Contents Association
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• v.18 no.9
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• pp.14-33
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• 2018

The purpose of this study to analyze the informatization trends in Korea through objective newspaper data for the period from 1998 to 2017 for informatization and library in four newspapers including KyoungHyang Newspaper, Kookmin Ilbo, Hankyoreh and Hankookilbo. Based on the analysis results of metadata and related words using BIGKinds, a news big data system, this study presented analysis of simple frequency, classification and classification of the keywords 'information', 'informatization' and 'library'. Based on the results, we compared and analyzed the tendency of informatization in the media through comparison with the 'Information White Paper' which is the publication of government agencies and with research about the research topic of 4 academic journals in the Library and Information Science field. This study tried to interpret the trends of informatization based on the media and it is meaningful that we analyzed the big data of newspaper article which is the long term and time series data. Based on the results of the study, implications of the growth and development of libraries with domestic informatization were suggested. It is expected that we will be able to create a basic framework for developing library informatization policy through the further studies.

• The Journal of the Korea Contents Association
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• v.17 no.1
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• pp.351-362
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• 2017

Recently, analysis techniques to extract new meanings using big data analysis and various services using them have been developed. A disaster safety service among such services has been paid attention as the most important service. In this paper, we design and implement a flood disaster safety system using real time weather big data. The proposed system retrieves and processes vast amounts of information being collected in real time. In addition, it analyzes risk factors by aggregating the collected real time and past data and then provides users with prediction information. The proposed system also provides users with the risk prediction information by processing real time data such as user messages and news, and by analyzing disaster risk factors such a typhoon and a flood. As a result, users can prepare for potential disaster safety risks through the proposed system.

• Journal of the Korean Data and Information Science Society
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• v.26 no.2
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• pp.409-418
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• 2015

With the development of mobile devices and Internet, information exchange has actively been made through SNS and Blogs. Blogs are widely used as a space where people share their experience after their visit to tourist attractions. We propose a method of recommending associated tourist attractions based on tourists' opinions using issue analysis, association analysis, and sentimental analysis for various online reviews including news in order to help to develop tour products and policies. The result shows that north area of Chungbuk province has been selected as issue attractions, and associated attractions/keywards have been identified for given well-known attraction. Positive/negative opinion for review texts has been analyzed and user can grasp the reason for the sentiments. Multidimensional analysis technique has been integrated to derive additional sophisticated insights and various policy proposal for smart tourism.

• The Journal of Information Systems
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• v.30 no.3
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• pp.21-45
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• 2021

Purpose This paper analyzed the impacts of domestic stock market by a global pandemic such as COVID-19. We investigated how the overall pattern of the stock market changed due to the impact of the COVID-19 pandemic. In particular, we analyzed in depth the pattern of stock price, as well, tried to find what factors affect on stock market index(KOSPI) in the healthcare industry due to the COVID-19 pandemic. Design/methodology/approach We built a data warehouse from the databases in various industrial and economic fields to analyze the changes in the KOSPI due to COVID-19, particularly, the changes in the healthcare industry centered on bio-medicine. We collected daily stock price data of the KOSPI centered on the KOSPI-200 about two years before and one year after the outbreak of COVID-19. In addition, we also collected various news related to COVID-19 from the stock market by applying text mining techniques. We designed four experimental data sets to develop decision tree-based prediction models. Findings All prediction models from the four data sets showed the significant predictive power with explainable decision tree models. In addition, we derived significant 10 to 14 decision rules for each prediction model. The experimental results showed that the decision rules were enough to explain the domestic healthcare stock market patterns for before and after COVID-19.

• Journal of The Korean Association of Information Education
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• v.25 no.6
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• pp.935-945
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• 2021

The purpose of this study is to analyze the social perception of Arduino lecture using big data analysis method. For this purpose, data from January 2012 to May 2021 were collected using the Textom website as a keyword searched for 'arduino + lecture' in blogs, cafes, and news channels of NAVER website. The collected data was refined using the Textom website, and text mining analysis and semantic network analysis were performed by opening the Textom website, Ucinet 6, and Netdraw programs. As a result of text mining analysis such as frequency analysis, TF-IDF analysis, and degree centrality it was confirmed that 'education' and 'coding' were the top keywords. As a result of CONCOR analysis for semantic network analysis, four clusters can be identified: 'Arduino-related education', 'Physical computing-related lecture', 'Arduino special lecture', and 'GUI programming'. Through this study, it was possible to confirm various meaningful social perceptions of the general public in relation to Arduino lecture on the Internet. The results of this study will be used as data that provides meaningful implications for instructors preparing for Arduino lectures, researchers studying the subject, and policy makers who establish software education or coding education and related policies.