• 한국도서관정보학회지
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• 제50권4호
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• pp.339-358
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• 2019

본 연구의 목적은 광의의 측면에서 지식정보제공이라는 공동의 임무를 수행하는 도서관, 기록관, 박물관간의 협력 플랫폼 구축에 관한 연구의 동향을 토픽 모델링을 통하여 파악하기 위한 것이다. 연구의 목적을 달성하기 위하여 Scopus로부터 이들 세 기관을 동시에 다루는 논문 637편의 서지정보를 수집하였다. 수집된 서지정보 중에서 초록을 대상으로 NetMiner V.4를 통하여 총 5,218개의 단어를 추출한 후 토픽모델링 분석하였으며, 그 결과는 다음과 같다. 첫째, tf-idf의 가중치에 따른 단어출현 빈도를 분석한 결과 '보존(Preservation)'이 가장 높게 나타났으며, 둘째, LDA(Latent Dirichlet Allocation) 알고리즘을 통한 토픽모델링 분석결과 13개의 주제 영역이 도출되었다. 셋째, 13개의 주제 영역을 네트워크로 표현한 결과 '리포지터리 구축(Repository Construction)'을 중심으로 기관간의 협력, 정보자원 보존을 위한 환경 구축, 정부차원에서의 제도와 정책 발굴, 정보자원의 생애주기, 정보자원의 전시, 정보자원의 검색 등이 서로 밀접한 관련성을 가진 것으로 나타났다. 넷째, 13개의 주제 영역의 연도별 동향을 살펴보면, 1998년 이전의 연구는 제도와 정책 발굴, 정보자원의 검색, 정보자원의 생애주기 등과 같이 특정 주제에 한정된 반면, 그 이후의 연구는 보다 다양한 주제를 다룬 것으로 분석되었다.

• 한국IT서비스학회지
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• 제15권2호
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• pp.169-184
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• 2016

Smartphone use is rapidly spreading due to the advantage of being able to connect to the Internet anytime, anywhere--and mobile app development is developing accordingly. The characteristic of the mobile app market is the ability to launch one's app into foreign markets with ease as long as the platform is the same. However, a large amount of prior research asserts that consumers behave differently depending on their culture and, from this perspective, various studies comparing the differences between consumer behaviors in different countries exist. Accordingly, this research, which uses online product reviews (OPRs) in order to analyze the cultural differences in consumer behavior comparatively by nationality, proposes to compare the U.S. and South Korea by selecting ten apps which were released in both countries in order to perform a sentimental analysis on the basis of star ratings and, based on those ratings, to interpret the sentiments in reviews. This research was carried out to determine whether, on the basis of ratings analysis, analysis of review contents for sentiment differences, analysis of LDA topic modeling, and co-occurrence analysis, actual differences in online reviews in South Korea and the U.S. exist due to cultural differences. The results confirm that the sentiments of reviews for both countries appear to be more negative than those of star ratings. Furthermore, while no great differences in high-raking review topics between the U.S. and South Korea were revealed through topic modeling and co-occurrence analyses, numerous differences in sentiment appeared-confirming that Koreans evaluated the mobile apps' specialized functions, while Americans evaluated the mobile apps in their entirety. This research reveals that differences in sentiments regarding mobile app reviews due to cultural differences between Koreans and Americans can be seen through sentiment analysis and topic modeling, and, through co-occurrence analysis, that they were able to examine trends in review-writing for each country.

• 공학교육연구
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• 제25권5호
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• pp.85-93
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• 2022

Capstone Design, a project-based learning technique, is the most important curriculum that clarifying major knowledge and cultivating the ability to apply through the process of solving problems in the industrial field centered on the student project team. Accordingly, various and extensive studies are being conducted for the successful implementation of capstone design courses. Unlike previous studies, this study aimed to quantitatively analyze the opinions that recorded the experiences and feelings of students who performed capstone design, and used text mining methodologies such as frequency analysis, correlation analysis, topic modeling, and sentiment analysis. As a result of examining the overall opinions of the latter period through frequency analysis and correlation analysis, there was a difference between the languages used by the students in the opinions according to gender and project results. Through topic modeling analysis, 'topic selection' and 'the relationship between team members' showed an increase in occupancy or high occupancy, and topics such as 'presentation', 'leadership', and 'feeling what they felt' showed a tendency to decreasing occupancy. Lastly, sentiment analysis has found that female students showed more neutral emotions than male students, and the passed group showed more negative emotions than the non-passed group and less neutral emotions. Based on these findings, students' practical recognition of the curriculum was considered and implications for the improvement of capstone design were presented.

• Journal of Multimedia Information System
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• 제1권1호
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• pp.55-67
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• 2014

Image topic and emotion analysis is an important component of online image retrieval, which nowadays has become very popular in the widely growing social media community. However, due to the gaps between images and texts, there is very limited work in literature to detect one image's Topics and Emotions in a unified framework, although topics and emotions are two levels of semantics that often work together to comprehensively describe one image. In this work, a unified model, Joint Topic/Emotion Multi-Modal Hierarchical Latent Dirichlet Allocation (JTE-MMHLDA) model, which extends previous LDA, mmLDA, and JST model to capture topic and emotion information at the same time from heterogeneous data, is proposed. Specifically, a two level graphical structured model is built to realize sharing topics and emotions among the whole document collection. The experimental results on a Flickr dataset indicate that the proposed model efficiently discovers images' topics and emotions, and significantly outperform the text-only system by 4.4%, vision-only system by 18.1% in topic detection, and outperforms the text-only system by 7.1%, vision-only system by 39.7% in emotion detection.

• 실내환경 및 냄새 학회지
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• 제17권4호
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• pp.322-329
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• 2018

The objective of this study is to identify the research trend in the field of indoor environment in Korea. We collected 419 papers published in the Journal of the Korean Society for indoor environment between 2004 and 2018, and attempted to produce datasets using a topic modeling technique, Latent Dirichlet Allocation(LDA). The result of topic modeling showed that 8 topics ("VOCs investigation", "Subway environment", "Building thermal environment", "School health", "Building particulate matter", "Asbestos risk", "Radon risk", "Air cleaner and treatment") could be extracted using Gibbs sampling method. In terms of topic trends, investigation of volatile organic compounds, subway environment, school health, and building particulate matter showed a decreasing tendency, while the building thermal environment, asbestos risk, radon risk, air cleaners, and air treatment showed an increasing tendency. The results of this topic modeling could help us to understand current trends related indoor environment, and provide valuable information in developing future research and policy frameworks.

• 한국정보전자통신기술학회논문지
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• 제15권5호
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• pp.423-432
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• 2022

본 논문은 학술연구자들이 COVID-19 관련 논문의 전체적인 연구 동향을 파악할 수 있도록 한다. KCI 사이트에서 수집한 2020년 1월부터 2022년 7월까지 총 10,599편의 COVID-19 관련 논문 정보를 LDA 토픽 모델링으로 분석한 결과를 제시한다. 또한 학술연구자들이 자신의 관심 연구분야의 토픽을 쉽게 파악할 수 있도록 LDA 토픽 모델링의 결과를 주요 연구 카테고리별로 분석하고, 토픽별로 연구가 많이 이루어지는 세부 연구 카테고리 정보를 분석한다. 학술연구자들이 시간의 흐름에 따른 연구 토픽의 추세(trend)를 파악하는 것은 연구 동향을 파악하는데 매우 중요하다. 따라서 이를 위해 본 논문에서는 시계열 분해를 사용하여 토픽들의 추세(trend)를 분석하여 제시한다.

• 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.

• 품질경영학회지
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• 제44권2호
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• pp.389-408
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• 2016

Purpose: This study was designed to analyze the behavioral change of knowledge structures and the trends of research topics in the quality management field. Methods: The network structure and knowledge structure of the words were visualized in map form using co-word analysis, cluster analysis and strategic diagram. Results: Summarizing the research results obtained in this study are as follows. First, the word network derived from co-occurrence matrix had 106 nodes and 5,314 links and its density was analyzed to 0.95. Average betweenness centrality of word network was 2.37. In addition, average closeness centrality and average eigenvector centrality of word network were 0.01. Second, by applying optimal criteria of cluster decision and K-means algorithm to word co-occurrence matrix, 106 words were grouped into seven clusters such as standard & efficiency, product design, reliability, control chart, quality model, 6 sigma, and service quality. Conclusion: According to the results of strategic diagram analysis over time, the traditional research topics of quality management field related to reliability, 6 sigma, control chart topics in the third quadrant were revealed to be declined for their study importance. Research topics related to product design and customer satisfaction were found to be an important research topic over analysis periods. Research topic related to management innovation was emerging state and the scope of research topics related to process model was extended to research topics with system performance. Research topic related to service quality located in the first quadrant was analyzed as the key research topic.

• 디지털융복합연구
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• 제19권12호
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• pp.11-20
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• 2021

본 연구는 신문기사 빅데이터를 통해 대학교육 관련 보도의 토픽을 추출하고, 토픽별 특징 및 신문사별 보도양상을 분석한다. 2016년-2021년 상반기 주요 중앙지와 지역지의 기사를 빅카인즈를 통해 추출하였고, 잠재디리슐레할당을 이용하여 총 9개의 토픽을 발견하였다. 토픽1과 토픽3은 교육에 대한 대학지원사업에 관련된 것이나 토픽3은 지역대학에 초점이 맞추어져 있다. 토픽2는 코로나19 이후 대학교육, 토픽4는 교수-학습법, 토픽5는 정부정책, 토픽6은 고교교육기여대학 지원사업, 토픽7은 대학교육 비전, 토픽8은 국제화, 토픽9는 입시 등을 논하고 있다. 조선일보, 경향신문, 한겨레는 코로나19 이후 강의, 정부정책 관련, 대학교육에 대한 기사와 논평을 많이 보도한 반면 동아일보, 중앙일보, 한라일보, 부산일보, 대전일보, 경인일보는 대학지원사업, 고교교육기여대학 지원사업 등 광고·홍보성 기사가 상대적으로 많았다. 2016년부터의 관련기사를 신문사별 뿐 아니라, COVID-19 발생 전후로도 분석하여 관련 보도의 토픽 차이를 살펴볼 수 있었다. 사회적으로 주요 관심 사항인 대학교육이 언론에 어떻게 보도되고 있는지 확인함으로써 미래의 대학교육 정책 방향과 미디어의 순기능과 역기능 등 언론의 역할에 대해 고찰할 필요가 있음을 시사한다.

• 정보화정책
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• 제30권1호
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• pp.41-66
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• 2023

본 연구는 72개 지자체의 74개 스마트시티 조례를 대상으로, 지자체 스마트시티 조례의 방향성을 확인하고자 토픽모델링을 활용하여 조례의 주요 키워드를 확인하고, 조례의 키워드에 따른 주제분류를 진행하였다. 분석결과 주요 키워드는 스마트도시위원회의 구성 및 운영에 관한 키워드가 조례 내에서 높은 빈도를 보였다. 조례에 대한 토픽모델링 Latent Dirichlet Allocation(LDA) 분석결과 관련 키워드에 따라 총 8개의 주제로 분류할 수 있었다. 구체적으로 주제-1(스마트시티 추진사항 보안), 주제-2(스마트시티 산업진흥), 주제-3(스마트시티 주민협의체 구성), 주제-4(스마트시티 추진체계 지원), 주제-5(개인정보 관리), 주제-6(스마트시티 데이터 활용), 주제-7(지능정보화 행정구현), 주제-8(스마트시티 홍보) 등으로, 주제의 비중은 주제-6, 주제-4, 주제-1 등의 순으로 나타났다. 권역별 주제분류는 수도권은 주제-5, 주제-6, 주제-8 의 비중이 높았고, 지방권은 주제-2, 주제-3, 주제-4의 비중이 높아 수도권은 스마트시티의 실질 운영 관련 주제가 높았고, 지방권은 스마트시티 추진을 위한 준비단계 관련 주제 비중이 높았다.