• Journal of The Korean Association of Information Education
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• v.25 no.4
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• pp.633-640
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• 2021

Education related issues are social problems in which various groups and situations are intricately linked to each other. It is difficult to find issues by analyzing social phenomena related to education. Korean based text analysis can be analyzed in a quantitative. With the development of text analysis techniques, research results have been recently achieved, and it can be fully utilized to derive educational issues from text data in Korean. In this study, petition articles in the field of childcare/education were collected on the online-board of the Blue House National Petition website, and text analysis was used to derive issues in the education world. The analysis derived 6 topics through Latent Dirichlet Allocation(LDA) among topic modeling techniques. The association rules of major keywords were analyzed and visualized as graphs. In addition to deriving educational issues through the existing questionnaire, it can provide implications for future research directions and policies in that issues can be sufficiently discovered through text-based analysis methods.

• The Journal of the Korea Contents Association
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• v.12 no.8
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• pp.207-214
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• 2012

The purpose of this study was to review the agreement and disagreement logics on privatization of health care to bring quality enhancement of medical service and alienated area without medical services at the same time, to identify the core keywords through language network analysis a kind of contents analysis on the editorials dealing with privatization of health care and hospitals for profit published on the major daily newspapers for the recent three years, and to find out what is the core of the controversy through the connection centrality analysis of core keywords. Conclusively, it was found from the centrality analysis that "medical service," "hospital," "privatization," "privatization of health care," "hospital for profit" and "Government" were situated in the center of the controversy. It is natural that keywords such as "medical service," "hospital," "privatization," "privatization of health care"and "hospital for profit" were located in the center because this study reviewed the editorials published on major newspapers for the recent three years regarding the privatization of health care or hospital for profit. Next important keywords (words) were "people," "health"and "health insurance." It shows that privatization of health care was not simply seen as the opening of medical service market but as an important issue related to health of people and health Insurance. Next words with high centrality were "objection" and "allowance." Through the contents analysis of editorials for the last three years, it was found that the opinions for and against the privatization were equally matched according to the centrality analysis result. On the other hand, there is one noticeable result in centrality analysis, which is the keywords such as "US," "Korea US" and "FTA" showed centrality to some extent. It shows privatization is handled relating US and Korea US FTA by editorials.

• Journal of Internet Computing and Services
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• v.17 no.6
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• pp.153-158
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• 2016

As the number of social network users increases, the information on event such as social issues and disasters receiving attention in each region is promptly posted by the bucket through social media site in real time, and its social ripple effect becomes huge. This study proposes a detection method of events that draw attention from users in specific region at specific time by using twitter data with regional information. In order to collect Twitter data, we use Twitter Streaming API. After collecting data, We implemented event detection system by analyze the frequency of a keyword which contained in a twit in a particular time and clustering the keywords that describes same event by exploiting keywords' co-occurrence graph. Finally, we evaluates the validity of our method through experiments.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10c
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• pp.267-272
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• 2006

인터넷망의 지속적인 발달과 함께 웹 애플리케이션 개발 방법으로 XML 기반의 웹 서비스가 부각되면서 많은 웹 서비스들이 개발되었고, 점차 더 많은 웹 서비스들이 개발될 것으로 예상된다. 이처럼 급격하게 늘어나는 웹 서비스들 중에서 사용자가 원하는 웹 서비스 찾는 것이 중요한 이슈로 부각되고 있다. 그러나 현재의 웹 서비스 검색 표준인 UDDI 레지스트리는 키워드 기반이기 때문에 검색 성능의 한계점을 갖고 있다. 최근에 이러한 한계를 극복하고자 하는 많은 연구가 진행되고 있지만 아직은 많이 부족한 상황이다. 따라서 본 논문에서는 비록 키워드가 일치하지 않더라도 사용자가 원하는 웹 서비스를 찾을 수 있도록 웹 서비스 표준인 UDDI 레지스트리에 시맨틱 매칭 엔진(semantic matching engine)이라는 추가적인 시맨틱 레이어를 추가하여 재현율(recall)과 정확률(precision)을 모두 향상 시킬 수 있는 시스템을 제안한다.

• Journal of the Korean Regional Science Association
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• v.39 no.4
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• pp.91-110
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• 2023

The purpose of this study is to explore urban issues that have arisen in the urban growth process of the 1st New Town for about 34 years since its construction through newspaper articles. For this purpose, newspaper articles related to the 1st New Town were collected using web crawling, and content analysis was conducted based on text mining. The main findings of the study are as follows. First, in the early stages of the construction of the 1st New Town, issues were diverse in the following six sectors: living service facilities, real estate, transportation, urban development and maintenance, safety, and housing supply, but gradually narrowed down to those of real estate and urban development and maintenance. Second, during the new town construction and urban stabilization stages, the network structure centered on 'Seoul' was maintained, which can be explained by the fact that the 1st New Town was geographically located on the outskirts of Seoul, and many articles compared the issues to Seoul. Third, the issue of urban aging appeared from the 10th year after construction, and the discussion on urban reorganization due to urban aging began in earnest from the 30th year after construction. The significance of the study is that it explored the urban issues that occurred throughout the urban growth process of the 1st New Town, and can be used as a basis for preparing a plan to reorganize the 1st New Town.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.2
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• pp.63-73
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• 2018

Academia and research institutes mainly use qualitative methods that rely on expert judgments to understand and predict research trends and science and technology trends. Since such a technique has the disadvantage of requiring much time and money, in this study, science and technology trends were predicted using keyword network analysis. To that end, 13,618 AI (Artificial Intelligence) patent abstracts were analyzed using keyword network analysis in three separate lots based on the period of the submission of each abstract: analysis period 1 (January 1, 2002 - December 31, 2006), analysis period 2 (January 1, 2007 - December 31, 2011), and analysis period 3 (January 1, 2012 - December 31, 2016). According to the results of frequency analyses, keywords related to methods in the field of AI application appeared more frequently as time passed from analysis period 1 to analysis period 3. In keyword network analyses, the connectivity between keywords related to methods in the field of AI application and other keywords increased over time. In addition, when the connected keywords that showed increasing or decreasing trends during the entire analysis period were analyzed, it could be seen that the connectivity to methods and management in the field of AI application was strengthened while the connectivity to the field of basic science and technology was weakened. According to analysis of keyword connection centrality, the centrality value of the field of AI application increased over time. According to analysis of keyword mediation centrality during analysis period 3, keywords related to methodologies in the field of AI application showed the highest mediation value. Therefore, it is expected that methods in the field of AI application will play the role of powerful intermediaries in AI hereafter. The technique presented in this paper can be employed in the excavation of tasks related to regional innovation or in fields such as social issue visualization.

• Knowledge Management Research
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• v.22 no.2
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• pp.145-165
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• 2021

As of late December 2019, the spread of COVID-19 pandemic began which put the entire world in panic. In order to overcome the crisis and minimize any subsequent damage, the government as well as its affiliated institutions must maximize effects of pre-existing policy support and introduce a holistic response plan that can reflect this changing situation- which is why it is crucial to analyze social topics and people's interests. This study investigates people's major thoughts, attitudes and topics surrounding COVID-19 pandemic through the use of social media and big data. In order to collect public opinion, this study segmented time period according to government countermeasures. All data were collected through NAVER blog from 31 December 2019 to 12 December 2020. This research applied TF-IDF keyword extraction and LDA topic modeling as text-mining techniques. As a result, eight major issues related to COVID-19 have been derived, and based on these keywords, this research presented policy strategies. The significance of this study is that it provides a baseline data for Korean government authorities in providing appropriate countermeasures that can satisfy needs of people in the midst of COVID-19 pandemic.

• Annual Conference of KIPS
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• 2019.05a
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• pp.2-4
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• 2019

인천공항은 2001년 개항이후, 비약적으로 발전하고 있으며, 2018년 약 6500만 명의 여객을 수용하는 등 초대형 메가허브공항으로 도약 중이다. 2018년 인천공항은 제2여객터미널을 개장하며, 인천공항에 대한 언론과 대중의 관심을 증폭시켰고, 평창동계올림픽 개최와 남북정상회담을 통해 대한민국 중추공항으로서의 이미지를 각인시켰다. 인천국제공항공사는 인천공항의 건설 및 관리, 운영, 주변지역개발, 부대사업 및 기타 국가위탁사업을 하는 국토교통부 산하 공공기관으로 2018년 입국장 면세점 도입, 정규직 전환 등의 이슈를 생성하였다. 본 논문에서는 뉴스, SNS 수집, 저장, 처리, 분석플랫폼인 ITAP를 이용하여 인천공항, 인천국제공항공사 관련된 뉴스, SNS 내용을 플랫폼별로 분석하였고, 월별 버즈량과 주요키워드를 플랫폼별로 추출하여 2018년 인천공항, 인천국제공항공사의 주요 이슈를 제시한다.

• Annual Conference of KIPS
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• 2024.05a
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• pp.503-504
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• 2024

미래사회는 데이터 활용이 곧 경쟁력으로 이를 해결하기 위한 방안으로 이슈 기술에 대한 IP(지적 재산) 정보를 수집하여 키워드와 특허분류를 이용하여 클러스터링한 결과물을 정보시스템으로 구축하는 지식플랫폼을 체계화하는 연구이다. 연구 대상은 바이오화학 산업으로 한정하고 성장성, 산업성, 영향력, 융합성을 적용하여 후보군 물질명을 도출, 관련된 특허정보를 클러스터링하는 지식플랫폼을 타 산업분야에서도 적용할 수 있도록 확장성을 고려하여 설계하였다.

• Electronics and Telecommunications Trends
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• v.26 no.4
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• pp.22-30
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• 2011

본 동향은 최근 이슈가 되고 있는 스마트TV 개발동향 및 시장전망에 대하여 알아보고, 스마트TV 검색 서비스에 대하여 소개한다. 스마트TV 검색 서비스는 사용자가 입력한 키워드 검색문의 의미를 해석하여 사용자가 의도하는 콘텐츠를 정확하게 찾아주는 시맨틱 기반 검색 서비스와 동일한 콘텐츠를 시청하고 있는 커뮤니티를 검색하여 콘텐츠에 대한 의견과 정보를 공유하는 소셜 네트워크 기반검색 서비스로 나누어 살펴본다.