• 지식경영연구
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• 제20권3호
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• pp.139-154
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• 2019

With the increasing use of smartphone apps, many apps are coming out in various fields. In order to analyze the current status and trends of apps in a specific field, it is necessary to establish a classification scheme. Various schemes considering users' behavior and characteristics of apps have been proposed, but there is a problem in that many apps are released and a fixed classification scheme must be updated according to the passage of time. Although it is necessary to consider many aspects in establishing classification scheme, it is possible to grasp the trend of the app through the proposal of a classification scheme according to the characteristic of the app. This research proposes a method of establishing an app classification scheme through the description of the app written by the app developers. For this purpose, we collected explanations about apps in the tourism field and identified major categories through topic modeling. Using only the apps corresponding to the topic, we construct a network of words contained in the explanatory text and identify subcategories based on the networks of words. Six topics were selected, and Clauset Newman Moore algorithm was applied to each topic to identify subcategories. Four or five subcategories were identified for each topic.

• International Journal of Internet, Broadcasting and Communication
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• 제12권4호
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• pp.204-211
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• 2020

The era of the 4th industrial revolution is a complex environment in which the cyber world and the physical world are integrated and interacted. In order to successfully implement and be sustainable the 4th industrial revolution of hyper-connectivity, hyper-convergence, and hyper-intelligence, not only the technological aspects that implemented digitalization but also the social aspects must be recognized and dealt with as important. There are socio-technical systems and socio-technical systems theory as concepts that describe systems involving complex interactions between the environmental aspects of human, mechanical and tissue systems. This study confirmed how the Socio-technical System was applied in the research literature for the last 10 years through machine learning-based analysis. Eight clusters were derived by performing co-occurrence keywords network analysis, and 13 research topics were derived and analyzed by performing a structural topic model. This study provides consensus and insight on the social and technological perspectives necessary for the sustainability of the 4th industrial revolution.

• Asian Journal of Innovation and Policy
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• 제6권3호
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• pp.262-273
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• 2017

Recently, the attention to the $4^{th}$ Industrial Revolution has been increasing. In the $4^{th}$ Industrial Revolution era, the boundaries between physical space, digital space, and biological space are becoming blurred because of the active convergence between various fields. There are many issues about the $4^{th}$ Industrial Revolution such as artificial intelligence, Internet of things, big data, and cyber physical system. To cope with the $4^{th}$ Industrial Revolution, an accurate analysis and technology planning need to be undertaken from a broad point of view. However, there is little research on the analysis of the major issues about the 4th Industrial Revolution. Accordingly, this study aims to analyse these major issues. Data mining such as topic modelling method is used for this analysis. This study is expected to be helpful for the researcher and policy maker of the 4th Industrial Revolution.

• International Journal of Advanced Culture Technology
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• 제11권4호
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• pp.378-384
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• 2023

In this study, we explore social awareness, interest, and acceptance of generative AI, including chatGPT, which has revolutionized web search, 30 years after web search was released. For this purpose, we performed a machine learning-based topic modeling analysis based on Korean news big data collected from November 30, 2022, when chatGPT was released, to August 31, 2023. As a result of our research, we have identified seven topics related to chatGPT and generative AI; (1)growth of the high-performance hardware market, (2)service contents using generative AI, (3)technology development competition, (4)human resource development, (5)instructions for use, (6)revitalizing the domestic ecosystem, (7)expectations and concerns. We also explored monthly frequency changes in topics to explore social interest related to chatGPT and Generative AI. Based on our exploration results, we discussed the high social interest and issues regarding generative AI. We expect that the results of this study can be used as a precursor to research that analyzes and predicts the diffusion of innovation in generative AI.

• Asia Marketing Journal
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• 제26권1호
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• pp.45-59
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• 2024

Extended Reality (XR) technology, the umbrella term covering hyper-realistic technologies, is known to enhance consumer experience and is therefore developing rapidly and being utilized across various industries. Growing studies have examined XR technology and consumer experience; however, the literature has failed to fully explore hyper-realistic technology through a holistic perspective. To fill this gap, we analyzed 720 Korean and international articles through semantic network analysis and topic modeling and identified the literature on XR research in consumer experience. As a result, we extracted six main topics: "Tourism," "Buying Behavior," "XR Technology Acceptance," "Virtual Space," "Game," and "XR Environment." The results provide comprehensive insight on XR technology in consumer experience, whereas the literature is bounded on the production side as revealing a lack of academic discourse on consumer rights and responsibilities. Research reflecting the consumer welfare perspective is, therefore, recommended for future studies.

• 동서간호학연구지
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• 제26권2호
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• pp.118-129
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• 2020

Purpose: The purpose of this study was to analyze the topic trend of domestic simulation nursing education research using text network analysis(TNA). Methods: This study was conducted in four steps. TNA was performed using the NetMiner (version 4.4.1) program. Firstly, 245 articles from 4 databases (RISS, KCI, KISS, DBpia) published from 2008 to 2018, were collected. Secondly, keyword-forms were unified and representative words were selected. Thirdly, co-occurrence matrices of keywords with a frequency of 2 or higher were generated. Finally, social network-related measures-indices of degree centrality and betweenness centrality-were obtained. The topic trend over time was visualized as a sociogram and presented. Results: 178 author keywords were extracted. Keywords with high degree centrality were "Nursing student", "Clinical competency", "Knowledge", "Critical thinking", "Communication", and "Problem-solving ability." Keywords with high betweenness centrality were "CPR", "Knowledge", "Attitude", "Self-efficacy", "Performance ability", and "Nurse." Over time, the topic trends on simulation nursing education have diversified. For example, topics such as "Neonatal nursing", "Obstetric nursing", "Pediatric nursing", "Blood transfusion", "Community visit nursing", and "Core basic nursing skill" appeared. The core-topics that emerged only recently (2017-2018) were "High-fidelity", "Heart arrest", "Clinical judgment", "Reflection", "Core basic nursing skill." Conclusion: Although simulation nursing education research has been increasing, it is necessary to continue studies on integrated simulation learning designs based on various nursing settings. Additionally, in simulation nursing education, research is required not only on learner-centered educational outcomes, but also factors that influence educational outcomes from the perspective of the instructors.

• 정보관리학회지
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• 제39권4호
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• pp.75-97
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• 2022

전통적인 학술 커뮤니케이션 체제의 문제점을 해결하기 위한 대안으로 오픈액세스 패러다임에 대한 국제적 관심과 확산이 지속되고 있다. 하지만 데이터 기반의 정량적인 방법을 통해 오픈액세스 분야의 글로벌한 동향이나 성장 추세를 파악하려는 노력은 아직까지 부족한 실정이다. 본 연구는 오픈액세스 분야의 학술논문 데이터에 토픽 모델링을 적용하여 세부 연구토픽을 식별하고, 성장곡선을 적합하여 각 연구토픽의 성숙도와 예상 잔여수명을 계산한다. 본 연구는 오픈 사이언스의 세 가지 핵심요소인 오픈액세스, 오픈데이터, 오픈협업과 관련된 14개 토픽들을 식별하였으며, 오픈액세스 분야가 앞으로 약 65년간 꾸준히 성장할 것으로 예상하였다. 본 연구의 분석 결과는 연구자들과 정책 의사결정자들이 오픈액세스 분야의 동향과 성장 추세를 이해하는 데 도움을 줄 수 있을 것으로 기대된다.

• 디지털융복합연구
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• 제18권2호
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• pp.139-149
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• 2020

새로운 플랫폼 정부는 지능적인 정보기술을 활용하여 정부와 국민이 서로 협력하는 새로운 생태계 기반 정부 혁신과 지속 가능한 발전을 견인하는 역할을 할 것이다. 이에 플랫폼 정부의 플랫폼 구축을 위해 최근 관련 연구 동향에 대해 살펴보고 향후 미래정책 방향 및 연구기반을 마련하기 위한 토대를 구축하고자 한다. 연구 분석을 위해 각 부처와 정부산하기관에서 발행된 연구보고서를 텍스트마이닝 기법을 활용하여 텍스트 자료를 수집하고, 수집된 텍스트 자료를 토픽 모델링과 네트워크 분석을 시행하였다. 분석결과 미래전략과 집단 내에서의 네트워크 연결이 제대로 이루워지지 않고 있으며 연결 중심성이 강할수록 관계성이 약해지는 것을 도출하였다. 이는 정부가 플랫폼을 설계하고 데이터와 서비스를 공급하는 공급 역할에서 통합적, 상호 교류적 접점이 필요하며 정부와 시민, 기업의 협치가 가능한 생태계가 조성되어야 할 것이다. 본 연구를 통해 플랫폼 정부의 공급과 수요적 접근의 이해를 높이고 잠재적 토픽에 따라 적절한 변경관리 방법을 구현하기 위한 논의가 다각적으로 이루어지길 기대한다.

• Journal of Information Processing Systems
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• 제19권1호
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• pp.55-66
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• 2023

Community portraits can deeply explore the characteristics of community structures and describe the personalized knowledge needs of community users, which is of great practical significance for improving community recommendation services, as well as the accuracy of resource push. The current community portraits generally have the problems of weak perception of interest characteristics and low degree of integration of topic information. To resolve this problem, the reader community portrait method based on the thematic and timeliness characteristics of interest labels (UIT) is proposed. First, community opinion leaders are identified based on multi-feature calculations, and then the topic features of their texts are identified based on the LDA topic model. On this basis, a semantic mapping including "reader community-opinion leader-text content" was established. Second, the readers' interest similarity of the labels was dynamically updated, and two kinds of tag parameters were integrated, namely, the intensity of interest labels and the stability of interest labels. Finally, the similarity distance between the opinion leader and the topic of interest was calculated to obtain the dynamic interest set of the opinion leaders. Experimental analysis was conducted on real data from the Douban reading community. The experimental results show that the UIT has the highest average F value (0.551) compared to the state-of-the-art approaches, which indicates that the UIT has better performance in the smooth time dimension.

• Educational Technology International
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• 제25권1호
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• pp.1-25
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• 2024

This study aims to analyze the impact of learners' usability perceptions of topic modeling-based visual feedback and generative AI interpretation on reflection levels in online discussions. To achieve this, we asked 17 students in the Department of Korean language education to conduct an online discussion. Text data generated from online discussions were analyzed using LDA topic modeling to extract five clusters of related words, or topics. These topics were then visualized in a network format, and interpretive feedback was constructed through generative AI. The feedback was presented on a website and rated highly for usability, with learners valuing its information usefulness. Furthermore, an analysis using the non-parametric Mann-Whitney U test based on levels of usability perception revealed that the group with higher perceived usability demonstrated higher levels of reflection. This suggests that well-designed and user-friendly visual feedback can significantly promote deeper reflection and engagement in online discussions. The integration of topic modeling and generative AI can enhance visual feedback in online discussions, reinforcing the efficacy of such feedback in learning. The research highlights the educational significance of these design strategies and clears a path for innovation.