• Title/Summary/Keyword: 빅데이터분석기사

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A study on frame transition of personal information leakage, 1984-2014: social network analysis approach (사회연결망 분석을 활용한 개인정보 유출 프레임 변화에 관한 연구: 1984년-2014년을 중심으로)

  • Jeong, Seo Hwa;Cho, Hyun Suk
    • Journal of Digital Convergence
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    • v.12 no.5
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    • pp.57-68
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    • 2014
  • This article analyses frame transition of personal information leakage in Korea from 1984 to 2014. In order to investigate the transition, we have collected newspaper article's titles. This study adopts classification, text network analysis(by co-occurrence symmetric matrix), and clustering techniques as part of social network analysis. Moreover, we apply definition of centrality in network in order to reveal the main frame formed in each of four periods. As a result, accessibility of personal information is extended from public sector to private sector. The boundary of personal information leakage is expanded to overseas. Therefore it is urgent to institutionalize the protection of personal information from a global perspective.

Analysis and Prediction of Trends for Future Education Reform Centering on the Keyword Extraction from the Research for the Last Two Decades (미래교육 혁신을 위한 트렌드 분석과 예측: 20년간의 문헌 연구 데이터를 기반으로 한 키워드 추출 분석을 중심으로)

  • Jho, Hunkoog
    • Journal of Science Education
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    • v.45 no.2
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    • pp.156-171
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    • 2021
  • This study aims at investigating the characteristics of trends of future education over time though the literature review and examining the accuracy of the framework for forecasting future education proposed by the previous studies by comparing the outcomes between the literature review and media articles. Thus, this study collects the articles dealing with future education searched from the Web of Science and categorized them into four periods during the new millennium. The new articles from media were selected to find out the present of education so that we can figure out the appropriateness of the proposed framework to predict the future of education. Research findings reveal that gradual tendencies of topics could not be found except teacher education and they are diverse from characteristics of agents (students and teachers) to the curriculum and pedagogical strategies. On the other hand, the results of analysis on the media articles focuses more on the projects launched by the government and the immediate responses to the COVID-19, as well as educational technologies related to big data and artificial intelligence. It is surprising that only a few key words are occupied in the latest articles from the literature review and many of them have not been discussed before. This indicates that the predictive framework is not effective to establish the long-term plan for education due to the uncertainty of educational environment, and thus this study will give some implications for developing the model to forecast the future of education.

Trend Analysis in Maker Movement Using Text Mining (텍스트 마이닝을 이용한 메이커 운동의 트렌드 분석)

  • Park, Chanhyuk;Kim, Ja-Hee
    • The Journal of the Korea Contents Association
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    • v.18 no.12
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    • pp.468-488
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    • 2018
  • The maker movement is a phenomenon of society and culture where people who make necessary things come together and share knowledge and experience through creativity. However, as the maker movement has grown rapidly over the past decade, there is still a lack of consensus for how far they will be viewed as a maker movement. We need to look at how the maker movement has changed so far in order to find the direction of development of the maker movement. This study analyzes the media articles using text-based big data analysis methodology to understand how the issue of the maker movement has changed in general media. In particular, we apply Keyword Network Analysis and DTM(Dynamic Topic Model) to analyze changes of interest according to time. The Keyword Network Analysis derives major keywords at the word level in order to analyze the evolution of the maker movement, and DTM helps to identify changes in interest in different areas of the maker movement at three levels: word, topic, and document. As a result, we identified major topics such as start-ups, makerspaces, and maker education, and the major keywords have changed from 3D printer and enterprise to education.

The Correlation between Social Media and the Behaviors of the Supreme Court in Korea (소셜미디어와 대법원 판결의 상관 관계에 대한 분석)

  • Heo, Junhong;Seo, Yeeun;Lee, Seoyeong;Lee, Sang-Yong Tom
    • Knowledge Management Research
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    • v.22 no.3
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    • pp.31-53
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    • 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.

News Big Data Analysis of 'Media Literacy' Using Topic Modeling Analysis (미디어 리터러시 뉴스 빅데이터 분석: 토픽 모델링 분석을 중심으로)

  • Han, Songlee;Kim, Taejong
    • The Journal of the Korea Contents Association
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    • v.21 no.4
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    • pp.26-37
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    • 2021
  • This study conducted a big data analysis on news to identify the agenda of media literacy, which has been socially discussed, and on which relevant policy directions will be proposed. To this end 1,336 articles from January 1, 2019 to September 30, 2020 were collected and a topic modeling analysis was conducted according to four periods. Five topics for each period were derived through the analysis, and implications based on the results are as follows. First, the government should implement a nation-level systematic approach to media literacy education according to life cycle stages to generate economic and cultural value. Second, local communities and schools should provide systematic support and education guidance activities to ensure a sustainable ecosystem for media literacy and prevent an educational gap and loss in learning. Third, efforts should be made in various aspects to minimize the side effects resulting from constantly providing media literacy education; furthermore a culture of desirable media application should be established. Finally, a research environment for scientific research on media literacy, active exchange of experience and value obtained in the field, and long-term accumulation of research results should be encouraged to develop a robust knowledge exchange culture.

Analysis of the Study Trend of Glass Ceiling by Period Using Text Mining (텍스트 마이닝을 이용한 시대별 유리천장 연구동향 분석)

  • Kim, Young-Man;Lee, Jin Gu
    • The Journal of the Korea Contents Association
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    • v.21 no.8
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    • pp.376-387
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    • 2021
  • This study is to analyze the research trends related to the 'glass ceiling' phenomenon using big data analysis methods and to suggest social implications. To analyze the research trends of 'glass ceiling', the historical event that broke the 'glass ceiling' was set as an important issue, and keywords were collected by dividing park's term into three. Before, throughout and after, her term. As a result of frequency analysis, research was conducted based on 'public servants' which was selected as the main keyword in the first period, while 'women's work family compatibility' was chosen as the main keyword group in the second period. In the third period, keywords for women's occupational groups were being diversified. As a result of applying CONCOR techniques to make the studied main topics grouped, we were able to confirm that the main issues were the differentiating factors, the customary gender discrimination culture, the jobs aimed for studying, the work-family balance, the glass ceiling and the organizational performance adjustment factors, the public sector, organizational performance, and the private sector. Besides work-family compatibility support system, it was suggested as a social implication that research on improving the system to resolve the glass ceiling factor and to expand the target jobs to give solutions to real-life issues were needed, and also suggested that research on the 'glass ceiling' which the general public perceives through social medias or articles in the news, was needed in the future.

Study on the Analysis of National Paralympics by Utilizing Social Big Data Text Mining (소셜 빅데이터 텍스트 마이닝을 활용한 전국장애인체육대회 분석 연구)

  • Kim, Dae kyung;Lee, Hyun Su
    • 한국체육학회지인문사회과학편
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    • v.55 no.6
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    • pp.801-810
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    • 2016
  • The purpose of the study was to conduct a text mining examining keywords related to the National Paralympics and provide the fundamental information that would be used to change perception of people without disabilities toward disabilities and to promote the social participation of people with and without disabilities in the National Paralympics. Social big data regarding the National Paralympics were retrieved from news articles and blog postings identified by search engines, Naver, Daum, and Google. The data were then analysed using R-3.3.1 Version Program. The analysing techniques were cloud analysis, correlation analysis and social network analysis. The results were as follows. First, news were mainly related to game results, sports events, team participation and host avenue of the 33rd ~ 36th National Paralympics. Second, search results about the 33rd ~ 36th National Paralympics between Naver, Daum, and Google were similar to one another. Thirds, the keywrods, National Paralympics, sports for the disabled, and sports, demonstrated a high close centrality. Further, degree centrality and betweenness centrality were associated in the keywords such as sports for all, participation, research, development, sports-disabled, research-disabled, sports for all-participation, disabled-participation, sports for all-disabled, and host-paralympics.

Korea National College of Agriculture and Fisheries in Naver News by Web Crolling : Based on Keyword Analysis and Semantic Network Analysis (웹 크롤링에 의한 네이버 뉴스에서의 한국농수산대학 - 키워드 분석과 의미연결망분석 -)

  • Joo, J.S.;Lee, S.Y.;Kim, S.H.;Park, N.B.
    • Journal of Practical Agriculture & Fisheries Research
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    • v.23 no.2
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    • pp.71-86
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    • 2021
  • This study was conducted to find information on the university's image from words related to 'Korea National College of Agriculture and Fisheries (KNCAF)' in Naver News. For this purpose, word frequency analysis, TF-IDF evaluation and semantic network analysis were performed using web crawling technology. In word frequency analysis, 'agriculture', 'education', 'support', 'farmer', 'youth', 'university', 'business', 'rural', 'CEO' were important words. In the TF-IDF evaluation, the key words were 'farmer', 'dron', 'agricultural and livestock food department', 'Jeonbuk', 'young farmer', 'agriculture', 'Chonju', 'university', 'device', 'spreading'. In the semantic network analysis, the Bigrams showed high correlations in the order of 'youth' - 'farmer', 'digital' - 'agriculture', 'farming' - 'settlement', 'agriculture' - 'rural', 'digital' - 'turnover'. As a result of evaluating the importance of keywords as five central index, 'agriculture' ranked first. And the keywords in the second place of the centrality index were 'farmers' (Cc, Cb), 'education' (Cd, Cp) and 'future' (Ce). The sperman's rank correlation coefficient by centrality index showed the most similar rank between Degree centrality and Pagerank centrality. The KNCAF articles of Naver News were used as important words such as 'agriculture', 'education', 'support', 'farmer', 'youth' in terms of word frequency. However, in the evaluation including document frequency, the words such as 'farmer', 'dron', 'Ministry of Agriculture, Food and Rural Affairs', 'Jeonbuk', and 'young farmers' were found to be key words. The centrality analysis considering the network connectivity between words was suitable for evaluation by Cd and Cp. And the words with strong centrality were 'agriculture', 'education', 'future', 'farmer', 'digital', 'support', 'utilization'.

An Analysis of Fishing Village Tourism Issues Reported in Korea Media (국내 언론에 보도된 어촌관광 이슈의 변동 분석)

  • Ji-Yeong Ko;Chae-wan Lee
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.30 no.4
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    • pp.299-307
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    • 2024
  • Fishing villages, which are the focus of this study, are interested in fishing tourism for creating a new income base and sustaining fishing communities. This is because the extraordinary nature of the fishing village space creates new values in line with the function of tourism, however, the related policies are less than adequate compared to the importance of fishing village tourism. Therefore, this study aims to analyze the interest of Korean society in fishing village tourism the manner in which this issue has changed over time. Using the news analysis system, BigKinds, we systematically collected and analyzed articles related to fishing village tourism reported in the domestic media. The results showed that social interest in fishing village tourism and government policy support had increased over time, suggesting that fishing village tourism was an important strategy that could revitalize local economies and prevent the disappearance of fishing villages.

A study on the effect of tax evasion controversy on corporate values in internet news portals through big data analysis (빅데이터 분석을 통한 인터넷 뉴스 포털에서의 탈세 논란이 기업 가치에 미치는 영향 연구)

  • Lee, Sang-Min;Park, Myung-Ho;Kim, Byung-Jun;Park, Dae-Keun
    • Journal of Internet Computing and Services
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    • v.22 no.6
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    • pp.51-57
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    • 2021
  • If a company's actions to save or avoid taxes are judged to be tax evasion rather than legal tax action by the tax authorities, the company will not only pay tax but also non-tax costs such as damage to corporate image and stock price decline due to a series of tax evasion-related news articles. Therefore, this study measures the frequency of occurrence of tax evasion controversial keywords in internet news portal as a factor to measure the severity of the case, and analyzes the effect of the frequency of occurrence on corporate value. In the Korean stock market, we crawl related articles from internet news portal by using keywords that are controversial for tax evasion targeting top companies based on market capitalization, and generate a time series of the frequency of occurrence of keywords about tax evasion by company and analyze the effect of frequency of appearance on book value versus market capitalization. Through panel regression and impulse response analysis, it is analyzed that the frequency of appearance has a negative effect on the market capitalization and the effect gradually decreases until 12 months. This study examines whether the tax evasion issue affects the corporate value of Korean companies and suggests that it is necessary to take these influences into account when entrepreneurs set up tax-planning schemes.