• International Journal of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.179-184
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• 2024

Franchise are now a red ocean in Food industry and they need to find other options to appeal for their product, the uprising content, food tech. The franchises are working on R&D to help franchisees with the operations. Through this paper, we analyze the franchise interest on food tech and to help find the necessity of development for franchisees who are in needs with hand, not of human, but of technology. Using Textom, a big data analysis tool, "franchise" and "food tech" were selected as keywords, and search frequency information of Naver and Daum was collected for a year from 01 January, 2023 to 31 December, 2023, and data preprocessing was conducted based on this. For the suitability of the study and more accurate data, data not related to "food tech" was removed through the refining process, and similar keywords were grouped into the same keyword to perform analysis. As a result of the word refining process, a total of 10,049 words were derived, and among them, the top 50 keywords with the highest relevance and search frequency were selected and applied to this study. The top 50 keywords derived through word purification were subjected to TF-IDF analysis, visualization analysis using Ucinet6 and NetDraw programs, network analysis between keywords, and cluster analysis between each keyword through Concor analysis. By using big data analysis, it was found out that franchise do have interest on food tech. "technology", "franchise", "robots" showed many interests and keyword "R&D" showed that franchise are keen on developing food tech to seize competitiveness in Franchise Industry.

• Asian Journal of Innovation and Policy
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• v.9 no.2
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• pp.145-163
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• 2020

The COVID-19 is a pandemic that affects all facets of our life and will change many patterns in science technology and innovation. A qualitative study was conducted using Focus Group Interview involving ten industry-academia-research experts with the objective of identifying changes in Korea's national innovation system and science & technology policy after the COVID-19. Eight questions were designed, based on the major components of the national innovation system, such as companies, universities, and research institutes, to discuss the changes in the national innovation system and science & technology policy. Also, keyword analysis and cluster analysis were performed using the network analysis program VOSviewer. It is predicted that, in the wake of the COVID-19, Korea's national innovation system will shift to a new paradigm that is more decentralized, responsive, and autonomous. Furthermore, several policy agendas that can turn these changes into positive momentum of change in science & technology policy are presented.

• Annual Conference on Human and Language Technology
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• 2011.10a
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• pp.79-82
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• 2011

본 논문은 다양한 주제 분야의 연구 성과물을 제공하는 학술DB에서 주제어(Keyword) 정보를 바탕으로 SNA(Social Network Analysis)기법을 적용해 검색어와 연관도가 높은 연관검색어를 제공하는 것을 그 목적으로 한다. 이를 위해 주제어들 간의 가중치(Weight)를 계산한 뒤 Ego Network 분석을 통해 검색어와 연관된 연관주제어를 추출하고 이를 기존 학술DB에서 제공한 연관검색어와 비교 정리하였다. 그리고 정리된 결과를 연관규칙 마이닝기법, 유사계수를 적용해 연관도측면에서 비교 평가하였다.

• Journal of the Korea Society of Computer and Information
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• v.24 no.7
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• pp.135-141
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• 2019

The purpose of this study is to extract the key words from the list of research subjects related to 'hotel workers' published in recent 10 years(2009~2018) by using the language network analysis method and to confirm the relation between the key words. In this paper, we propose a semantic network analysis that can overcome limitations of longitudinal study, analyze the recent research trends, and widely use as a research model. The results of this study are as follows ; First, in analyzing major key words in the title of 'Hotel Employer' in recent 10 years, the major keyword of job satisfaction(40), special grade(26), organizational commitment(20), emotional labor(19), service(12), restaurant(10), and turnover intention(9). Second, we analyzed the relation of language network among major key words extracted from the study title of 'hotel workers'. Such a research process is expected to grasp the trends of research related to 'hotel workers' and give implications for the future direction of related research.

• The Journal of Information Systems
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• v.33 no.2
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• pp.81-103
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• 2024

Purpose The purposes of the study are to explore the overall theories used in e-commerce adoption research for small enterprises, to demonstrate the research topics and the growth of the research topics in e-commerce adoption for small businesses over twenty years by co-word analysis and to suggest future directions on e-commerce adoption research in small enterprises. Design/methodology/approach This study used bibliometrics approach to systematically review electronic commerce adoption in small enterprises. More specifically, the study used co-citation to reveal the structure and theoretical foundations and keyword network analysis to understand the changes of research themes in small business e-commerce adoption research from 1999 to 2023. Findings According to the bibliometrics analysis result, this study revealed the nine research topics in small enterprise e-commerce adoption. In addition, this study can be applied to start e-commerce adoption research on small enterprises with a theoretical framework.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.1
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• pp.1-10
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• 2018

Current evaluation practices for IT projects suffer from several problems, which include the difficulty of self-explanation for the evaluation results and the improperly scaled scoring system. This study aims to develop a methodology of opinion mining to extract key factors for the causal relationship analysis and to assess the feasibility of quantifying evaluation scores from text comments using opinion mining based on big data analysis. The research has been performed on the domain of publicly procured IT proposal evaluations, which are managed by the National Procurement Service. Around 10,000 sets of comments and evaluation scores have been gathered, most of which are in the form of digital data but some in paper documents. Thus, more refined form of text has been prepared using various tools. From them, keywords for factors and polarity indicators have been extracted, and experts on this domain have selected some of them as the key factors and indicators. Also, those keywords have been grouped into into dimensions. Causal relationship between keyword or dimension factors and evaluation scores were analyzed based on the two research models-a keyword-based model and a dimension-based model, using the correlation analysis and the regression analysis. The results show that keyword factors such as planning, strategy, technology and PM mostly affects the evaluation result and that the keywords are more appropriate forms of factors for causal relationship analysis than the dimensions. Also, it can be asserted from the analysis that evaluation scores can be composed or calculated from the unstructured text comments using opinion mining, when a comprehensive dictionary of polarity for Korean language can be provided. This study may contribute to the area of big data-based evaluation methodology and opinion mining for IT proposal evaluation, leading to a more reliable and effective IT proposal evaluation method.

• The Journal of the Korea Contents Association
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• v.16 no.8
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• pp.278-291
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• 2016

This study examined research trends via network analyses of keywords appeared in academic research articles about news reports in South Korea during the last 10 years from 2006 to 2015. Keyword network analyses of 4410 keywords from 1108 articles suggested that framing, agenda setting, third-person effect, selective exposure, and uses and gratification were main theories but most studies used framing theory. Research areas included news reports on politics, economics, science, world issues, or tour. However, research on news reports covering culture, sports or daily life were not identified. In terms of media, research on both traditional and emerging media were ample. Research on broadcasting new, online news, and social media were frequently observed.

• ETRI Journal
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• v.40 no.6
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• pp.745-758
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• 2018

A wide range of studies in various disciplines has focused on the Internet of Things (IoT) and cyber-physical systems (CPS). However, it is necessary to summarize the current status and to establish future directions because each study has its own individual goals independent of the completion of all IoT applications. The absence of a comprehensive understanding of IoT and CPS has disrupted an efficient resource allocation. To assess changes in the knowledge structure and emerging technologies, this study explores the dynamic research trends in IoT by analyzing bibliographic data. We retrieved 54,237 keywords in 12,600 IoT studies from the Scopus database, and conducted keyword frequency, co-occurrence, and growth-rate analyses. The analysis results reveal how IoT technologies have been developed and how they are connected to each other. We also show that such technologies have diverged and converged simultaneously, and that the emerging keywords of trust, smart home, cloud, authentication, context-aware, and big data have been extracted. We also unveil that the CPS is directly involved in network, security, management, cloud, big data, system, industry, architecture, and the Internet.

• Journal of the Korea Institute of Building Construction
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• v.20 no.6
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• pp.577-584
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• 2020

Construction automation and robotics have been widely adopted in the construction industry as a promising solution to such issues like a shortage of skilled labor and the difficulties workers face in harsh working environments. The analysis of the knowledge structure and its evolution from the existing articles helps identify essential knowledge elements and possible future research directions. This study attempts to (1) construct keyword networks from the papers published in the International Symposium on Automation and Robotics in Construction (ISARC), (2) investigate how keywords and keyword communities are associated with each other, and (3) examine the changes in the crucial keywords over time. Through cluster analysis, 79 keywords were categorized into four groups (BIM, Building construction, Sensing, and GPS as representative keywords) with similar structural positions. Research trends show that research themes related to Infrastructure, Construction equipment, and 3D have consistently received a large amount of attention, regardless of geographical region. Research on as-built status model utilization through BIM and Laser scanning and improving Energy performance is taking place more frequently. In contrast, research studies related to problem-solving based on Neural networks are not as common as previously. This study provides useful insights into the construction automation field, at both the macro and micro levels.

• Human Ecology Research
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• v.59 no.2
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• pp.245-259
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• 2021

The purpose of this study was to analyze big data to identify the sub-dimensions of ethical consumption, as well as the consumption value associated with ethical consumption that changes over time. For this study, data were collected from Naver and Daum using the keyword 'ethical consumption' and frequency and matrix data were extracted through Textom, for the period January 1, 2016, to December 31, 2018. In addition, a two-way mode network analysis was conducted using the UCINET 6.0 program and visualized using the NetDraw function. The results of text mining show increasing keyword frequency year-on-year, indicating that interest in ethical consumption has grown. The sub-dimensions derived for 2014 and 2015 are fair trade, ethical consumption, eco-friendly products, and cooperatives and for 2016 are fair trade, ethical consumption, eco-friendly products and animal welfare. The results of deriving consumption value keywords were classified as emotional value, social value, functional value and conditional value. The influence of functional value was found to be growing over time. Through network analysis, the relationship between the sub-dimensions of ethical consumption and consumption values derived each year from 2014 to 2018 showed a significantly strong correlation between eco-friendly product consumption and emotional value, social value, functional value and conditional value.