• 한국정보시스템학회지:정보시스템연구
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• 제26권4호
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• pp.327-353
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• 2017

Purpose Social media such as social network services, online forums, and customer reviews have produced a plethora amount of information online. Yet, the information deluge has created both opportunities and challenges at the same time. This research particularly focuses on the challenges in order to discover and track the service defects over time derived by mining publicly available online customer reviews. Design/methodology/approach Synthesizing the streams of research from text analytics, we apply two stages of methods of sentiment analysis and structural topic model incorporating meta-information buried in review texts into the topics. Findings As a result, our study reveals that the research framework effectively leverages textual information to detect, prioritize, and categorize service defects by considering the moving trend over time. Our approach also highlights several implications theoretically and practically of how methods in computational linguistics can offer enriched insights by leveraging the online medium.

• Journal of Information Processing Systems
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• 제18권3호
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• pp.359-373
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• 2022

The new crown pneumonia (COVID-19) has become a global epidemic. The disease has spread to most countries and poses a challenge to the healthcare system. Contact tracing technology is an effective way for public health to deal with diseases. Many experts have studied traditional contact tracing and developed digital contact tracking. In order to better understand the field of contact tracking, it is necessary to analyze the development of contact tracking in the field of computer science by bibliometrics. The purpose of this research is to use literature statistics and topic analysis to characterize the research literature of contact tracking in the field of computer science, to gain an in-depth understanding of the literature development status of contact tracking and the trend of hot topics over the past decade. In order to achieve the aforementioned goals, we conducted a bibliometric study in this paper. The study uses data collected from the Scopus database. Which contains more than 10,000 articles, including more than 2,000 in the field of computer science. For popular trends, we use VOSviewer for visual analysis. The number of contact tracking documents published annually in the computer field is increasing. At present, there are 200 to 300 papers published in the field of computer science each year, and the number of uncited papers is relatively small. Through the visual analysis of the paper, we found that the hot topic of contact tracking has changed from the past "mathematical model," "biological model," and "algorithm" to the current "digital contact tracking," "privacy," and "mobile application" and other topics. Contact tracking is currently a hot research topic. By selecting the most cited papers, we can display high-quality literature in contact tracking and characterize the development trend of the entire field through topic analysis. This is useful for students and researchers new to field of contact tracking ai well as for presenting our results to other subjects. Especially when comprehensive research cannot be conducted due to time constraints or lack of precise research questions, our research analysis can provide value for it.

• 한국콘텐츠학회논문지
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• 제21권12호
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• pp.47-56
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• 2021

본 연구는 네트워크 분석을 활용하여 대학생 인성 관련 연구의 동향을 파악하고 향후 연구 방향의 시사점을 제공하는데 그 목적이 있다. 이러한 연구목적을 위해 국내 학술지에 게재된 대학생 인성 관련 논문 194편을 대상으로 하였다. 연구결과를 정리하면 다음과 같다. 첫째, 대학생 인성 관련 연구는 2004년부터 발표되기 시작하여 2012년에 소폭 상승하였고, 2015년부터 상승곡선을 이어가다 2017년에 정점을 찍은 후, 하향추세인 것으로 확인된다. 둘째, 연결 중심성과 매개 중심성 분석에서 공통적으로 가장 높은 중심성을 가진 핵심 키워드는 '사회'와 '함양'이었다. 셋째, 1기(2004년-2010년)에는 개인적 차원과 인성의 인지적인 측면의 키워드, 2기(2011년-2015년)에는 사회적인 차원과 인성의 정서적인 측면의 키워드, 3기(2016년-2020년)에는 사회적인 차원과 인성의 인지·정서·행동적인 측면의 키워드가 핵심적이었다. 넷째, 토픽모델링 분석결과, 능력, 생활, 대인, 만족, 적응의 키워드로 이루어진 토픽 2와 역량, 도덕, 시민, 사회, 실천으로 이루어진 토픽 1이 가장 높은 비중을 차지하였다. 다섯째, 1기에는 토픽 4 단독, 2기에는 토픽 1과 토픽 2의 순으로, 3기에는 토픽 2와 토픽 1의 순으로 높은 비중을 차지하는 것으로 나타났다. 본 연구는 대학생 인성 관련 연구에 유용한 근거자료가 될 것이다.

• 무역학회지
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• 제47권4호
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• pp.137-159
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• 2022

This study aims to analyze international trade papers published in Korea during the past 2002-2022 years. Through this study, it is possible to understand the main subject and direction of research in Korea's international trade field. As the research mythologies, this study uses the big data analysis such as the text mining and Social Network Analysis such as frequency analysis, several centrality analysis, and topic analysis. After analyzing the empirical results, the frequency of key word is very high in trade, export, tariff, market, industry, and the performance of firm. However, there has been a tendency to include logistics, e-business, value and chain, and innovation over the time. The degree and closeness centrality analyses also show that the higher frequency key words also have been higher in the degree and closeness centrality. In contrast, the order of eigenvector centrality seems to be different from those of the degree and closeness centrality. The ego network shows the density of business, sale, exchange, and integration appears to be high in order unlike the frequency analysis. The topic analysis shows that the export, trade, tariff, logstics, innovation, industry, value, and chain seem to have high the probabilities of included in several topics.

• Journal of Korea Trade
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• 제24권8호
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• pp.171-188
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• 2020

Purpose - This is an exploratory study that aims to apply text mining techniques, which computationally extracts words from the large-scale text data, to legal documents to quantify trade claim contents and enables statistical analysis. Design/methodology - This is designed to verify the validity of the application of text mining techniques as a quantitative methodology for trade claim studies, that have relied mainly on a qualitative approach. The subjects are 81 cases of arbitration and court judgments from China published on the website of the UNCITRAL where the CISG was applied. Validation is performed by comparing the manually analyzed result with the automatically analyzed result. The manual analysis result is the cluster analysis wherein the researcher reads and codes the case. The automatic analysis result is an analysis applying text mining techniques to the result of the cluster analysis. Topic modeling and semantic network analysis are applied for the statistical approach. Findings - Results show that the results of cluster analysis and text mining results are consistent with each other and the internal validity is confirmed. And the degree centrality of words that play a key role in the topic is high as the between centrality of words that are useful for grasping the topic and the eigenvector centrality of the important words in the topic is high. This indicates that text mining techniques can be applied to research on content analysis of trade claims for statistical analysis. Originality/value - Firstly, the validity of the text mining technique in the study of trade claim cases is confirmed. Prior studies on trade claims have relied on traditional approach. Secondly, this study has an originality in that it is an attempt to quantitatively study the trade claim cases, whereas prior trade claim cases were mainly studied via qualitative methods. Lastly, this study shows that the use of the text mining can lower the barrier for acquiring information from a large amount of digitalized text.

• 융합보안논문지
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• 제22권5호
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• pp.61-67
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• 2022

본 연구의 목적은 인공지능의 연구동향을 분석하는 것이다. 입체적인 분석을 위하여 인공지능에 대한 사회과학에서의 연구방향과 공학에서의 연구방향의 차이를 객관적으로 비교하여 제시하고자 시도하였다. 연구방법은 빅데이터 분석방법론 중에서 토픽모델링을 활용하였으며, 분석데이터는 학술연구정보시스템에서 인공지능(AI)라는 키워드로 검색된1000개의 영문 논문을 활용하였다. 분석결과 사회과학분야에서는 인공지능에 대하여 '인간', '영향', '미래'라는 키워드를 중심으로 형성된 그룹을 확인할 수 있었고, 공학분야에서는 '인공지능 기반의 기술개발', '시스템', '위험-보안' 등의 그룹이 형성되었다.

• 벤처창업연구
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• 제17권3호
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• pp.245-256
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• 2022

본 연구는 토픽모델링과 동시출현단어 분석을 이용하여 기업가정신에 대한 연구 동향을 제공하는 것이 목적이다. 이를 위해 Web of Science 데이터베이스에서 'entrepreneurship'을 기본검색어로 설정하고, 2002년부터 2021년까지 발표한 14,953편의 기업가정신 논문의 데이터를 확보하였다. 본 연구에서는 VOSviewer 프로그램을 이용하여 동시출현단어 분석을 하였고, R 프로그램을 이용하여 토픽모델링 분석을 하였다. 본 연구의 분석결과는 다음과 같다. 첫째, 동시출현단어 분석 결과, 기업가정신과 혁신 클러스터, 기업가정신 교육 클러스터, 사회적 기업가정신과 지속가능성 클러스터, 기업성과 클러스터, 그리고 지식 및 기술이전 클러스터 등 5개의 클러스터로 구분되었다. 둘째, 토픽모델링 분석 결과, 창업환경 및 경제발전, 국제 기업가정신, 다양한 기업가정신, 벤처기업과 자본조달, 정부정책 및 지원, 사회적 기업가정신, 경영관련 이슈, 지역도시계획 및 개발, 기업가정신 교육, 기업가의 혁신과 성과, 기업가정신 연구, 기업가의 창업의도 등 12개의 토픽으로 분석되었다. 마지막으로, 시기별 토픽변화 추이 분석결과, 벤처기업과 자본조달과 기업가의 창업의도에 대한 토픽은 상승토픽으로 나타났고, 국제 기업가정신은 하강토픽으로 나타났다. 본 연구의 결과는 기업가정신 연구에 대한 전반적인 연구동향을 파악할 뿐만 아니라, 기업가정신 연구에 대한 통찰력을 제공하는데 유용할 것으로 기대된다.

• 한국문헌정보학회지
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• 제53권3호
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• pp.273-289
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• 2019

본 논문은 국내 다문화 관련 분야의 연구동향을 규명하기 위하여 다문화와 관련한 국내 학술 문헌을 수집하여 LDA (Latent Dirichlet Allocation) 기반의 토픽 모델링을 통해 토픽을 분석하였다. 이를 통해 국내 다문화 관련 연구에서의 중심 연구 토픽을 시기별로 추적하여 그 변화의 양상을 관찰하였고, 그 결과 핫 토픽으로는 '다문화 사회통합'과 '학교 다문화 교육'이 관찰되었으며 콜드 토픽으로는 '문화정체성과 민족주의' 관련 토픽이 관찰되었다.

• 한국정보시스템학회지:정보시스템연구
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• 제27권4호
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• pp.1-33
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• 2018

Purpose The purpose of this study is to review topic and survey methodological trends in 'The Journal of Information Systems' in order to present the practical guidelines for the future IS research. By attempting to conduct a meta-analysis on both topic and survey methodological trends, this study could provide researchers wishing to pursue this line of work further with what can be done to improve IS disciplines. Design/methodology/approach In this study, we have reviewed 185 papers that were published in 'The Journal of Information Systems' from 2010 to 2018 and classified them based on topics studied and survey methodologies used. The classification guidelines, which was developed by Palvia et al.(2015), has been used to capture the topic trends. We have also employed Struab et al.(2004)s' guidelines for securing rigor of validation issues. By using two guidelines, this study could also present topic and rigor trends in 'The Journal of Information Systems' and compare them to those trends in International Journals. Findings Our findings have identified dominant research topics in 'The Journal of Information Systems'; 1) social media and social computing, 2) IS usage and adoption, 3) mobile computing, 4) electronic commerce/business, 5) security and privacy, 6) supply chain management, 7) innovation, 8) knowledge management, and 9) IS management and planning. This study also could offer researchers who pursue this line of work further practical guidelines on mandatory (convergent and discriminant validity, reliability, and statistical conclusion validity), highly recommended (common method bias testing), and optional validations (measurement invariance testing for subgroup analysis, bootstrapping methods for testing mediating effects).

• 무역학회지
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• 제45권3호
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• pp.55-69
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• 2020

This study examines the research trends and knowledge structure of international trade studies using topic modeling method, which is one of the main methodologies of text mining. We collected and analyzed English abstracts of 1,868 papers of three Korean major journals in the area of international trade from 2003 to 2019. We used the Latent Dirichlet Allocation(LDA), an unsupervised machine learning algorithm to extract the latent topics from the large quantity of research abstracts. 20 topics are identified without any prior human judgement. The topics reveal topographical maps of research in international trade and are representative and meaningful in the sense that most of them correspond to previously established sub-topics in trade studies. Then we conducted a regression analysis on the document-topic distributions generated by LDA to identify hot and cold topics. We discovered 2 hot topics(internationalization capacity and performance of export companies, economic effect of trade) and 2 cold topics(exchange rate and current account, trade finance). Trade studies are characterized as a interdisciplinary study of three agendas(i.e. international economy, International Business, trade practice), and 20 topics identified can be grouped into these 3 agendas. From the estimated results of the study, we find that the Korean government's active pursuit of FTA and consequent necessity of capacity building in Korean export firms lie behind the popularity of topic selection by the Korean researchers in the area of int'l trade.