• Title/Summary/Keyword: 키워드분석

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Keywords and Topic Analysis of Social Issues on Twitter Based on Text Mining and Topic Modeling (텍스트 마이닝과 토픽 모델링을 기반으로 한 트위터에 나타난 사회적 이슈의 키워드 및 주제 분석)

  • Kwak, Soo Jeong;Kim, Hyon Hee
    • KIPS Transactions on Software and Data Engineering
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    • v.8 no.1
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    • pp.13-18
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    • 2019
  • In this study, we investigate important keywords and their relationships among the keywords for social issues, and analyze topics to find subjects of the social issues. In particular, we collected twitter data with the keyword 'metoo' which has attracted much attention in these days, and perform keyword analysis and topic modeling. First, we preprocess the twitter data, identified important keywords, and analyzed the relatedness of the keywords. After then, topic modeling is performed to find subjects related to 'metoo'. Our experimental results showed that relatedness of keywords and subjects on social issues in twitter are well identified based on keyword analysis and topic modeling.

Extracting week key issues and analyzing differences from realtime search keywords of portal sites (포털사이트 실시간 검색키워드의 주간 핵심 이슈 선정 및 차이 분석)

  • Chong, Min-Yeong
    • Journal of Digital Convergence
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    • v.14 no.12
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    • pp.237-243
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    • 2016
  • Since realtime search keywords of portal sites are arranged in descending order by instant increasing rates of search numbers, they easily show issues increasing in interests for a short time. But they have the limits extracted different results by portal sites and not shown issues by a period. Thus, to find key issues from the whole realtime search keywords for certain period, and to show results of summarizing them and analyzing differences, is significant in providing the basis of understanding issues more practically and in maintaining consistency of them. This paper analyzes differences of week key issues extracted from week analysis of realtime search keywords provided by two typical portal sites. The results of experiments show that the portal group means of realtime search keywords by the independent t-test and the survival functions of realtime search keywords by the survival analysis are statistically significant differences.

Keyword Network Analysis on Global Research Trend in Design (1999~2018) (글로벌 디자인 연구동향에 대한 키워드 네트워크 분석 연구 (1999~2018))

  • Choi, Chool-Heon;Jang, Phill-Sik
    • Journal of Convergence for Information Technology
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    • v.9 no.2
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    • pp.7-16
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    • 2019
  • The purpose of this study is to identify the characteristics of researches that have been conducted for the last 20 years through analyzing global research trends and evolutions of design articles from 1999 to 2018 with keyword network analysis. For this purpose, we selected 3,569 articles in 22 journals related to design research retrieved from the Scopus database and constructed keyword network model through the author keyword and index keyword. The frequency of the author and index keyword, the centrality of betweenness and degree were analyzed with the keyword network. The results show that design has been applied to various fields for recent 20 years, and the research trends of design could be quantitatively characterized by keyword network analysis. The result of this study could be used to suggest future research topics in the field of design based on quantitative and empirical data.

Analysis on the author keywords in the scientific articles (과학기술 논문의 저자 키워드 분석)

  • Kim, Tae-Jung;Lee, Seok-Hyoung;Kim, Kwang-Young;Kim, Hwanmin
    • Proceedings of the Korea Contents Association Conference
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    • 2014.11a
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    • pp.53-54
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    • 2014
  • 대부분 국내에서 발행되는 과학기술 분야의 논문에는 저자 키워드가 포함되어 있다. 이 키워드는 논문을 이해를 돕고 온라인 검색에 유용하게 활용되고 있다. 특히 많은 논문에서 키워드를 영문과 국문을 동시에 부여하도록 하고 있어 과학기술 용어로서의 가치도 있다. 일정 기간 국내에서 발행되는 논문으로부터 저자 키워드들을 추출하여 다양한 각도에서 부여 키워드의 현황을 분석하였다. 결론으로 바람직한 키워드 부여의 방향을 제시한다.

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Analysis of Trends in Science and Technology using Keyword Network Analysis (키워드 네트워크 분석을 활용한 과학기술동향 분석)

  • Park, Ju Seop;Kim, Na Rang;Han, Eun Jung
    • 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.

Research Trend Analysis of 'International Commerce and Information Review' Using SNA-based Keyword Network Analysis (SNA 기반 키워드 네트워크 분석을 활용한 '통상정보연구'의 연구동향 분석)

  • Yang, Kunwoo
    • International Commerce and Information Review
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    • v.19 no.1
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    • pp.23-42
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    • 2017
  • International Commerce and Information Review has been playing an important role of disseminating the outstanding research results in the fields such as trade information and systems, e-trade, regional studies, e-commerce, service trade, trade laws since 1999. This paper aims to find the research trends and distinguished characteristics in the field of trade information by analyzing research keywords of the research papers published in this journal using a social network analysis method. Research keyword data collected from the homepage of the academic society were cleaned and transformed into the co-occurrence network data, which are suitable for social network analysis. NodeXL Pro was used to analyze and visualize the pre-processed data. Through clustering analysis, the most important subject fields or interests were identified as well as those which worked as intermediaries for interdisciplinary researches.

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Research Trends Analysis on the Mediterranean Area Studies using Co-appearance Keywords (동시 출현 키워드를 활용한 지중해지역 연구 동향 분석)

  • Lee, Dong-Yul;Kang, Ji-Hoon;Moon, Sang-Ho
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.6 no.5
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    • pp.409-419
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    • 2016
  • In general, Area studies have very flexible field of research, so it is very difficult to proceed all field of research at the same time. Due to this, researches on Area studies have been changed the field of research and research trends according to age. So it is important to identify research trends for performing Area studies. Also, interests for understanding the research trend of Area studies are increasing constantly. In this paper, we analyze research trends of Mediterranean Area studies in Korea by using co-appearance keywords. To do this, we first analyze article types and extract co-appearance keywords on articles of 『Journal of Mediterranean Area Studies』, which is the representative journal of Mediterranean region in Korea. In details, trends analysis of Mediterranean Area studies would be performed by using cp-keywords of article and visualizing network graph forms.

A Keyword Analysis of Collection Development Policies of University and Public Libraries Using Text Mining (텍스트 마이닝을 활용한 대학도서관과 공공도서관의 장서개발 정책 키워드 분석)

  • Da-Hyeon Lee;Dong-Hee Shin
    • Journal of the Korean Society for Library and Information Science
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    • v.58 no.1
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    • pp.285-302
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    • 2024
  • For this article, we conducted frequency analysis, topic modeling, and network analysis on eleven texts related to collection development policy found in the National Library of Korea. We deduced the main keywords related to collection development policies and analyzed the relationship between them. We subsequently conducted a pie coefficient analysis to identify the characteristics of collection development policies of university libraries and public libraries by category. The results showed that keywords such as "material," "library," "collection development," "user," and "collection" were the main keywords in frequency analysis and network centrality. Meanwhile, the pie coefficient analysis revealed that keywords such as "university," "construction," "student," "target," and "cost" were prevalent in university libraries, indicating that the academic needs of users and the discussion of digital resources were primary issues, while keywords related to the information needs of various user groups-including "adults," "survey," "feature," and "religion" -appeared in public libraries.

An Analysis of Research Trends on Public Libraries in Korea Using Keyword Network Analysis (키워드 네트워크 분석을 활용한 국내 공공도서관 연구 동향 분석)

  • Rosa Chang
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.34 no.4
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    • pp.285-302
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    • 2023
  • Based on this study, the research trends were identified for the field of public libraries in Korea by utilizing the keyword network analysis. For 20 years from 2003 to 2022, a total of 752 papers related to the public libraries published in the four largest academic journals in the field of library and information science in Korea were analyzed. The research results are as follows. First, from 2003 to 2022, an annual average of 37.6 papers were published, demonstrating a pattern of repeated rise and fall. Second, the keywords of 'service' and 'culture' were identified as the most discussed keywords as they were found to be among the top five in terms of the frequency of occurrence, connection centrality, and the mediation centrality analysis results. Third, in terms of the results of analyzing the co-occurrence frequency of keyword pairs, attention was paid to the keyword pairs of education-program, service-user, service-children, and service-disability.

Implementation of summarization system for documents by using a word co-occurrence graph (단어의 공기 관계 그래프를 이용한 문서 요약 시스템의 구현)

  • Ryu, Je;Sun, Bok-Keun;Park, Boh-A;Han, Kwang-Rok
    • Proceedings of the Korean Information Science Society Conference
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    • 2000.04b
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    • pp.348-350
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    • 2000
  • 본 논문은 문서의 내용을 요약하기 위한 시스템의 구현에 대해서 다룬다. 문서의 내용을 분석하기 위해서는 문서의 키워드를 추출하고, 추출된 키워드를 사용하여 문서의 핵심 내용을 찾는 두 가지의 작업이 이루어져야 한다. 본 논문에서는 키워드를 추출하기 위해 형태소 분석 및 전처리기, 그리고 단어의 공기 관계 그래프를 이용한 키워드 추출기를 이용하였으며, 추출된 키워드를 이용하여 문서의 핵심 문장을 찾아내는 핵심 문장 추출기, 그리고 추출된 문장을 분석하여 내용을 요약할 수 있도록 해주는 구문분석기가 이용된다.

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