• Title/Summary/Keyword: Online mining

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A Study on the Research Trends on Domestic Platform Government using Topic Modeling (토픽 모델링을 활용한 한국의 플랫폼정부 연구동향 분석)

  • Suh, Byung-Jo;Shin, Sun-Young
    • Informatization Policy
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    • v.24 no.3
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    • pp.3-26
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    • 2017
  • The amount of unstructured data generated online is increasing exponentially and the analysis of text data is being done in various fields. In order to identify the research trends on the platform government, the title, year, academic society, and abstract information of the academic papers on the subject of platform government were collected from the database of the domestic papers, DBPIA(www.dbpia.co.kr). The results of the existing research on the platform government and related fields were analyzed based on each stage of the national informatization promotion. The technology, service, and governance topics were extracted from papers on platform government and the trends of core topics were analyzed by year. Entering the era of the intelligent information society, this study has significance for providing the basis for defining a new role of government - the platform government that sets the stage for the private sector to lead the innovation, and plays the role of an 'enabler' and 'facilitator' instead. The purpose of this study is to understand the platform government research through objective analysis of its trends. Looking for future directions, this study will contribute to future research by providing reference materials.

A Study on the Privacy Awareness through Bigdata Analysis (빅데이터 분석을 통한 프라이버시 인식에 관한 연구)

  • Lee, Song-Yi;Kim, Sung-Won;Lee, Hwan-Soo
    • Journal of Digital Convergence
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    • v.17 no.10
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    • pp.49-58
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    • 2019
  • In the era of the 4th industrial revolution, the development of information technology brought various benefits, but it also increased social interest in privacy issues. As the possibility of personal privacy violation by big data increases, academic discussion about privacy management has begun to be active. While the traditional view of privacy has been defined at various levels as the basic human rights, most of the recent research trends are mainly concerned only with the information privacy of online privacy protection. This limited discussion can distort the theoretical concept and the actual perception, making the academic and social consensus of the concept of privacy more difficult. In this study, we analyze the privacy concept that is exposed on the internet based on 12,000 news data of the portal site for the past one year and compare the difference between the theoretical concept and the socially accepted concept. This empirical approach is expected to provide an understanding of the changing concept of privacy and a research direction for the conceptualization of privacy for current situations.

A Topic Analysis of Abstracts in Journal of Korean Data Analysis Society (한국자료분석학회지에 대한 토픽분석)

  • Kang, Changwan;Kim, Kyu Kon;Choi, Seungbae
    • Journal of the Korean Data Analysis Society
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    • v.20 no.6
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    • pp.2907-2915
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    • 2018
  • Journal of the Korean Data Analysis Society founded in 1998 has played the role of a major application journal. In this study, we checked the objective of this journal by checking the abstracts for 10 years. Abstract data was crawled from the online journal site (kdas.jems.or.kr) and analyzed by topic model. As a result, we found 18 topics from 2680 abstracts that had several contents, for example, nursing, marketing, economics, regression, factor analysis, data mining and statistical inferences. Topic1 (regression) is most frequent with 460 documents and we found the usefulness of regression in the applied science area. We confirmed the significant 10 association rules using by Fisher's exact test. Also, for exploring the trend of topics, we conducted the topic analysis for two periods which are 2006-2011 period and 2012-2016 period. We found that the control study was more frequent than survey study over time and regression and factor analysis were frequent regardless of time.

The Research Trend Analysis of the Korean Journal of Physical Education using Mecab-ko Morphology Analyzer (Mecab-ko 형태소 분석을 이용한 한국체육학회지 연구동향 분석)

  • Park, Sung-Geon;Kim, Wanseop;Lee, Dae-Taek
    • 한국체육학회지인문사회과학편
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    • v.56 no.6
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    • pp.595-605
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    • 2017
  • The purpose of this study is to investigate what kind of research fields are preferred by the researcher of the Korean Physical Education Society using the Mecab-ko morpheme analysis and whether there are differences in the interests of researchers between the humanities and social sciences and natural sciences. A total of the data collected for this study are 5,014 papers published online from March 2002 to March 2017 in the Korean Journal of Physical Education was collected. In this study, we used Mecab-ko morpheme analyzer to extract the keyword from the collected documents. As a result, the study found that the number of papers published in KAHPERD appeared to be decreasing. It was also that the main concern of researchers in KAHPERD toward was leisure, live sports and health were relatively higher than the improvement of performance. The research subjects that were interested in the research were women, middle-aged and elderly. The study found that researchers in the humanities and social sciences have shown interest in both traditional research and social interests, while researchers in the natural sciences have shown an interest in a deeper study of traditional research. In conclusion, in order to realize the revitalization of sports convergence research, it is necessary to establish standards for the field of study which should focus on the depth and breadth of research.

Spatial analysis based on topic modeling using foreign tourist review data: Case of Daegu (외국인 관광객 리뷰데이터를 활용한 토픽모델링 기반의 공간분석: 대구광역시를 사례로)

  • Jung, Ji-Woo;Kim, Seo-Yun;Kim, Hyeon-Yu;Yoon, Ju-Hyeok;Jang, Won-Jun;Kim, Keun-Wook
    • Journal of Digital Convergence
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    • v.19 no.8
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    • pp.33-42
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    • 2021
  • As smartphone-based tourism platforms have become active, policy establishment and service enhancement using review data are being made in various fields. In the case of the preceding studies using tourism review data, most of the studies centered on domestic tourists were conducted, and in the case of foreign tourist studies, studies were conducted only on data collected in some languages and text mining techniques. In this study, 3,515 review data written by foreigners were collected by designating the "Daegu attractions" keyword through the online review site. And LDA-based topic modeling was performed to derive tourism topics. The spatial approach through global and local spatial autocorrelation analysis for each topic can be said to be different from previous studies. As a result of the analysis, it was confirmed that there is a global spatial autocorrelation, and that tourist destinations mainly visited by foreigners are concentrated locally. In addition, hot spots have been drawn around Jung-gu in most of the topics. Based on the analysis results, it is expected to be used as a basic research for spatial analysis based on local government foreign tourism policy establishment and topic modeling. And The limitations of this study were also presented.

Research Trends and Knowledge Structure of Digital Transformation in Fashion (패션 영역에서 디지털 전환 관련 연구동향 및 지식구조)

  • Choi, Yeong-Hyeon;Jeong, Jinha;Lee, Kyu-Hye
    • Journal of Digital Convergence
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    • v.19 no.3
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    • pp.319-329
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    • 2021
  • This study aims to investigate Korean fashion-related research trends and knowledge structures on digital transformation through information-based approaches. Accordingly, we first identified the current status of the relevant research in Korean academic literature by year and journal; subsequently, we derived key research topics through network analysis, and then analyzed major research trends and knowledge structures by time. From 2010 to 2020, we collected 159 studies published on Korean academic platforms, cleansed data through Python 3.7, and measured centrality and network implementation through NodeXL 1.0.1. The results are as follows: first, related research has been actively conducted since 2016, mainly concentrated in clothing and art areas. Second, the online platform, AR/VR, appeared as the most frequently mentioned topic, and consumer psychological analysis, marketing strategy suggestion, and case analysis were used as the main research methods. Through clustering, major research contents for each sub-major of clothing were derived. Third, major subject by period was considered, which has, over time, changed from consumer-centered research to strategy suggestion, and design development research of platforms or services. This study contributes to enhancing insight into the fashion field on digital transformation, and can be used as a basic research to design research on related topics.

Proposal of Promotion Strategy of Mobile Easy Payment Service Using Topic Modeling and PEST-SWOT Analysis (모바일 간편 결제 서비스 활성화 전략 : 토픽 모델링과 PEST - SWOT 분석 방법론을 기반으로)

  • Park, Seongwoo;Kim, Sehyoung;Kang, Juyoung
    • Journal of Intelligence and Information Systems
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    • v.28 no.4
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    • pp.365-385
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    • 2022
  • The easy payment service is a payment and remittance service that uses a simple authentication method. As online transactions have increased due to COVID-19, the use of an easy payment service is increasing. At the same time, electronic financial industries such as Naver Pay, Kakao Pay, and Toss are diversifying the competition structure of the easy payment market; meanwhile overseas fintech companies PayPal and Alibaba have a unique market share in their own countries, while competition is intensifying in the domestic easy payment market, as there is no unique market share. In this study, the participants in the easy payment market were classified as electronic financial companies, mobile phone manufacturers, and financial companies, and a SWOT analysis was conducted on the representative services in each industry. The analysis examined the user reviews of Google Play Store via a topic modeling analysis, and it employed positive topics as strengths and negative topics as weaknesses. In addition, topic modeling was conducted by dividing news articles into political, economic, social, and technology (PEST) articles to derive the opportunities and threats to easy payment services. Through this research, we intend to confirm the service capabilities of easy payment companies and propose a service activation strategy that allows gaining the upper hand in the market.

Detecting Weak Signals for Carbon Neutrality Technology using Text Mining of Web News (탄소중립 기술의 미래신호 탐색연구: 국내 뉴스 기사 텍스트데이터를 중심으로)

  • Jisong Jeong;Seungkook Roh
    • Journal of Industrial Convergence
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    • v.21 no.5
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    • pp.1-13
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    • 2023
  • Carbon neutrality is the concept of reducing greenhouse gases emitted by human activities and making actual emissions zero through removal of remaining gases. It is also called "Net-Zero" and "carbon zero". Korea has declared a "2050 Carbon Neutrality policy" to cope with the climate change crisis. Various carbon reduction legislative processes are underway. Since carbon neutrality requires changes in industrial technology, it is important to prepare a system for carbon zero. This paper aims to understand the status and trends of global carbon neutrality technology. Therefore, ROK's web platform "www.naver.com." was selected as the data collection scope. Korean online articles related to carbon neutrality were collected. Carbon neutrality technology trends were analyzed by future signal methodology and Word2Vec algorithm which is a neural network deep learning technology. As a result, technology advancement in the steel and petrochemical sectors, which are carbon over-release industries, was required. Investment feasibility in the electric vehicle sector and technology advancement were on the rise. It seems that the government's support for carbon neutrality and the creation of global technology infrastructure should be supported. In addition, it is urgent to cultivate human resources, and possible to confirm the need to prepare support policies for carbon neutrality.

A School-tailored High School Integrated Science Q&A Chatbot with Sentence-BERT: Development and One-Year Usage Analysis (인공지능 문장 분류 모델 Sentence-BERT 기반 학교 맞춤형 고등학교 통합과학 질문-답변 챗봇 -개발 및 1년간 사용 분석-)

  • Gyeongmo Min;Junehee Yoo
    • Journal of The Korean Association For Science Education
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    • v.44 no.3
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    • pp.231-248
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    • 2024
  • This study developed a chatbot for first-year high school students, employing open-source software and the Korean Sentence-BERT model for AI-powered document classification. The chatbot utilizes the Sentence-BERT model to find the six most similar Q&A pairs to a student's query and presents them in a carousel format. The initial dataset, built from online resources, was refined and expanded based on student feedback and usability throughout over the operational period. By the end of the 2023 academic year, the chatbot integrated a total of 30,819 datasets and recorded 3,457 student interactions. Analysis revealed students' inclination to use the chatbot when prompted by teachers during classes and primarily during self-study sessions after school, with an average of 2.1 to 2.2 inquiries per session, mostly via mobile phones. Text mining identified student input terms encompassing not only science-related queries but also aspects of school life such as assessment scope. Topic modeling using BERTopic, based on Sentence-BERT, categorized 88% of student questions into 35 topics, shedding light on common student interests. A year-end survey confirmed the efficacy of the carousel format and the chatbot's role in addressing curiosities beyond integrated science learning objectives. This study underscores the importance of developing chatbots tailored for student use in public education and highlights their educational potential through long-term usage analysis.

Online Privacy Protection: An Analysis of Social Media Reactions to Data Breaches (온라인 정보 보호: 소셜 미디어 내 정보 유출 반응 분석)

  • Seungwoo Seo;Youngjoon Go;Hong Joo Lee
    • Knowledge Management Research
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    • v.25 no.1
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    • pp.1-19
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    • 2024
  • This study analyzed the changes in social media reactions of data subjects to major personal data breach incidents in South Korea from January 2014 to October 2022. We collected a total of 1,317 posts written on Naver Blogs within a week immediately following each incident. Applying the LDA topic modeling technique to these posts, five main topics were identified: personal data breaches, hacking, information technology, etc. Analyzing the temporal changes in topic distribution, we found that immediately after a data breach incident, the proportion of topics directly mentioning the incident was the highest. However, as time passed, the proportion of mentions related indirectly to the personal data breach increased. This suggests that the attention of data subjects shifts from the specific incident to related topics over time, and interest in personal data protection also decreases. The findings of this study imply a future need for research on the changes in privacy awareness of data subjects following personal data breach incidents.