• Title/Summary/Keyword: Word Clouding

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Exploration of Research Trends in The Journal of Distribution Science Using Keyword Analysis

  • YANG, Woo-Ryeong
    • The Journal of Industrial Distribution & Business
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    • v.10 no.8
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    • pp.17-24
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    • 2019
  • Purpose - The purpose of this study is to find out research directions for distribution and fusion and complex field to many domestic and foreign researchers carrying out related academic research by confirming research trends in the Journal of Distribution Science (JDS). Research Design, Data, and Methodology - To do this, I used keywords from a total of 904 papers published in the JDS excluding 19 papers that were not presented with keywords among 923. The analysis utilized word clouding, topic modeling, and weighted frequency analysis using the R program. Results - As a result of word clouding analysis, customer satisfaction was the most utilized keyword. Topic modeling results were divided into ten topics such as distribution channels, communication, supply chain, brand, business, customer, comparative study, performance, KODISA journal, and trade. It is confirmed that only the service quality part is increased in the weighted frequency analysis result of applying to the year group. Conclusion - The results of this study confirm that the JDS has developed into various convergence and integration researches from the past studies limited to the field of distribution. However, JDS's identity is based on distribution. Therefore, it is also necessary to establish identity continuously through special editions of fields related to distribution.

Evaluation of Facilitating Factors for Cloud Service by Delphi Method (델파이 기법을 이용한 클라우드 서비스의 개념 정의와 활성화 요인 분석)

  • Suh, Jung-Han;Chang, Suk-Gwon
    • Journal of Information Technology Services
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    • v.11 no.2
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    • pp.107-118
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    • 2012
  • Recently, as the clouding computing begins to receive a great attention from people all over the world, it became the most popular buzz word in recent IT magazines or journal and heard it in many different services or different fields. However, a notion of the cloud service is defined vaguely compared to increasing attentions from others. Generally the cloud service could be understood as a specific service model base on the clouding computing, but the cloud, the cloud computing, the cloud computing service and cloud service, these four all terms are often used without any distinction of its notions and characteristics so that it's difficult to define the exact nature of the cloud service. To explore and analyze the cloud service systematically, an accurate conception and scope have to be preceded. Therefore this study is to firstly clarify its definition by Delpi method using expert group and then tries to provide the foundation needed to enable relative research such as establishing business model or value chain and policies for its activation to set off. For the Delpi, 16 experts participated in several surveys from different fields such industry, academy and research sector. As a result of the research, Characteristics of the Cloud Service are followings : Pay per use, Scalability, Internet centric Virtualization. And the scope as defined including Grid Computing, Utility Computing, Server Based Computing, Network Computing.

A Study on Leadership Trends from the Perspective of Domestic Researcher's Using BERTopic and LDA

  • Sung-Su, SHIN;Hoe-Chang, Yang
    • East Asian Journal of Business Economics (EAJBE)
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    • v.11 no.1
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    • pp.53-71
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    • 2023
  • Purpose - This study aims to find clues necessary for the direction of leadership development suitable for the current situation by exploring the direction in which leadership has been studied from the perspective of domestic researchers, along with the arrangement of leadership theories studied in various ways. Research design, data, and methodology - A total of 7,425 papers were obtained due to the search, and 5,810 papers with English abstracts were used for analysis. For analysis, word frequency analysis, word clouding, and co-occurrence were confirmed using Python 3.7. In addition, after classifying topics related to research trends through BERTopic and LDA, trends were identified through dynamic topic modeling and OLS regression analysis. Result - As a result of the BERTopic, 14 topics such as 'Leadership management and performance' and 'Sports leadership' were derived. As a result of conducting LDA on 1,976 outliers, five topics were derived. As a result of trend analysis on topics by year, it was confirmed that five topics, such as 'military police leadership' received relative attention. Conclusion - Through the results of this study, a study on the reinterpretation of past leadership studies, a study on LMX with an expanded perspective, and a study on integrated leadership sub-factors of modern leadership theory were proposed.

Overseas Research Trends Related to 'Research Ethics' Using LDA Topic Modeling

  • YANG, Woo-Ryeong;YANG, Hoe-Chang
    • Journal of Research and Publication Ethics
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    • v.3 no.1
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    • pp.7-11
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    • 2022
  • Purpose: The purpose of this study is to derive clues about the development direction of research ethics and areas of interest which has recently become a social issue in Korea by confirming overseas research trends. Research design, data and methodology: We collected 2,760 articles in scienceON, which including 'research ethics' in their paper. For analysis, frequency analysis, word clouding, keyword association analysis, and LDA topic modeling were used. Results: It was confirmed that many of the papers were published in medical, bio, pharmaceutical, and nursing journals and its interest has been continuously increasing. From word frequency analysis, many words of medical fields such as health, clinical, and patient was confirmed. From topic modeling, 7 topics were extracted such as ethical policy development and human clinical ethics. Conclusions: We founded that overseas research trends on research ethics are related to basic aspects than Korea. This means that a fundamental approach to ethics and the application of strict standards can become the basis for cultivating an overall ethical awareness. Therefore, academic discussions on the application of strict standards for publishing ethics and conducting researches in various fields where community awareness and social consensus are necessary for overall ethical awareness.

Topic Modeling of News Article Related to Franchise Regulation Using LDA (LDA 를 이용한 '프랜차이즈 규제' 관련 뉴스기사 토픽모델링)

  • YANG, Woo-Ryeong;YANG, Hoe Chang
    • The Korean Journal of Franchise Management
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    • v.13 no.4
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    • pp.1-12
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    • 2022
  • Purpose: In 2020, the franchise industry accomplished a significant growth compared to the previous year, as the number of franchise companies increased by 9.0% while the number of franchise brands increased by 12.5%. Despite growth in size, the Korean franchise industry underwent many negative incidents, such as franchise ownership sales to private equity funds, that led to deterioration of businesses. From this point of view, this study aims to make various proposals to help policy makers develop franchise industry policies by analyzing trends of the current and previous presidential administrations' franchise policies and regulations using newspaper articles. Research design, data and methodology: A total of 7,439 articles registered in Naver API from February 25, 2013 to November 29, 2021 were extracted. Among them, 34 unrelated video articles were deleted, and a total of 7,405 articles from both administrations were used for analysis. The R package was used for word frequency analysis, word clouding, word correlation analysis, and LDA (Latent Dirichlet Allocation) topic modeling. Results: The keyword frequency analysis shows that the most frequently mentioned keywords during the previous administration include 'no-brand', 'major company', 'bill', 'business field', and 'SMEs', and those mentioned during the current administration include 'industry' and 'policy'. As a result of LDA topic modeling, 9 topics such as 'global startups' and 'job creation' from the previous administration, and 10 topics such as 'franchise business' and 'distribution industry' from the current administration were derived. The results of LDAvis showed that the previous administration operated a policy based on mutual growth of large and small businesses rather than hostile regulations in the franchise business, whereas the current administration extended the regulation related to franchise business to the employment sector. Conclusions: The analysis of past two administrations' franchise policy, it can be suggested that franchisors and franchisees may complement each other in developing the Fair Transactions in Franchise Business Act and achieving balanced growth. Moreover, political support is needed for sound development of franchisors. Limitations and future research suggestions are presented at the end of this study.

Korean Collective Intelligence in Sharing Economy Using R Programming: A Text Mining and Time Series Analysis Approach (R프로그래밍을 활용한 공유경제의 한국인 집단지성: 텍스트 마이닝 및 시계열 분석)

  • Kim, Jae Won;Yun, You Dong;Jung, Yu Jin;Kim, Ki Youn
    • Journal of Internet Computing and Services
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    • v.17 no.5
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    • pp.151-160
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    • 2016
  • The purpose of this research is to investigate Korean popular attitudes and social perceptions of 'sharing economy' terminology at the current moment from a creative or socio-economic point of view. In Korea, this study discovers and interprets the objective and tangible annual changes and patterns of sociocultural collective intelligence that have taken place over the last five years by applying text mining in the big data analysis approach. By crawling and Googling, this study collected a significant amount of time series web meta-data with regard to the theme of the sharing economy on the world wide web from 2010 to 2014. Consequently, huge amounts of raw data concerning sharing economy are processed into the value-added meaningful 'word clouding' form of graphs or figures by using the function of word clouding with R programming. Till now, the lack of accumulated data or collective intelligence about sharing economy notwithstanding, it is worth nothing that this study carried out preliminary research on conducting a time-series big data analysis from the perspective of knowledge management and processing. Thus, the results of this study can be utilized as fundamental data to help understand the academic and industrial aspects of future sharing economy-related markets or consumer behavior.

A Study of Consumer Perception on Fashion Show Using Big Data Analysis (빅데이터를 활용한 패션쇼에 대한 소비자 인식 연구)

  • Kim, Da Jeong;Lee, Seunghee
    • Journal of Fashion Business
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    • v.23 no.3
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    • pp.85-100
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    • 2019
  • This study examines changes in consumer perceptions of fashion shows, which are critical elements in the apparel industry and a means to represent a brand's image and originality. For this purpose, big data in clothing marketing, text mining, semantic network analysis techniques were applied. This study aims to verify the effectiveness and significance of fashion shows in an effort to give directions for their future utilization. The study was conducted in two major stages. First, data collection with the key word, "fashion shows," was conducted across websites, including Naver and Daum between 2015 and 2018. The data collection period was divided into the first- and second-half periods. Next, Textom 3.0 was utilized for data refinement, text mining, and word clouding. The Ucinet 6.0 and NetDraw, were used for semantic network analysis, degree centrality, CONCOR analysis and also visualization. The level of interest in "models" was found to be the highest among the perception factors related to fashion shows in both periods. In the first-half period, the consumer interests focused on detailed visual stimulants such as model and clothing while in the second-half period, perceptions changed as the value of designers and brands were increasingly recognized over time. The findings of this study can be utilized as a tool to evaluate fashion shows, the apparel industry sectors, and the marketing methods. Additionally, it can also be used as a theoretical framework for big data analysis and as a basis of strategies and research in industrial developments.

A Study on the Consumer's Perception of HiSeoul Fashion Show Using Big Data Analysis (빅데이터 분석을 활용한 하이서울패션쇼에 대한 소비자 인식 조사)

  • Han, Ki Hyang
    • Journal of Fashion Business
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    • v.23 no.5
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    • pp.81-95
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    • 2019
  • The purpose of this study is to research consumers' perception of the HiSeoul fashion show, which is being used by new designers as a means of promotion, and to propose a strategy for revitalizing new designer brands. This was done in order to secure basic data from fashion consumers, to help guide marketing strategies and promote rising designers. In this research, the consumers' perception of HiSeoul fashion show was verified using text-mining, data refinement and word clouding that was undertaken by TEXTOM3.0. Also, semantic network analysis, CONCOR analysis and visualization of the analysis results were performed using Ucinet 6.0 and NetDraw. "HiSeoul fashion show" was used as the keyword for text-mining and data was collected from March 1, 2018 to April 30, 2019. Using frequency analysis, TF-IDF, and N-gram, it was also shown that consumers are aware of places where shows are held, such as DDP and Igansumun. It was also revealed that consumers recognize rising designer brands, designer's names, the names of guests attending the show and the photo times. This study is meaningful in that it not only confirmed consumers' interest in new designer brands participating in the HiSeoul Fashion Show through big data but also confirmed that it is available as a marketing strategy to boost brand sales. This study suggests using HiSeoul show room to induce consumer sales, or inviting guests that match the brand image to promote them on SNS on the day the show is held for a marketing strategy.

A Longitudinal Study on Customers' Usable Features and Needs of Activity Trackers as IoT based Devices (사물인터넷 기반 활동량측정기의 고객사용특성 및 욕구에 대한 종단연구)

  • Hong, Suk-Ki;Yoon, Sang-Chul
    • Journal of Internet Computing and Services
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    • v.20 no.1
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    • pp.17-24
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    • 2019
  • Since the information of $4^{th}$ Industrial Revolution is introduced in WEF (World Economic Forum) in 2016, IoT, AI, Big Data, 5G, Cloud Computing, 3D/4DPrinting, Robotics, Nano Technology, and Bio Engineering have been rapidly developed as business applications as well as technologies themselves. Among the diverse business applications for IoT, wearable devices are recognized as the leading application devices for final customers. This longitudinal study is compared to the results of the 1st study conducted to identify customer needs of activity trackers, and links the identified users' needs with the well-known marketing frame of marketing mix. For this longitudinal study, a survey was applied to university students in June, 2018, and ANOVA were applied for major variables on usable features. Further, potential customer needs were identified and visualized by Word Cloud Technique. According to the analysis results, different from other high tech IT devices, activity trackers have diverse and unique potential needs. The results of this longitudinal study contribute primarily to understand usable features and their changes according to product maturity. It would provide some valuable implications in dynamic manner to activity tracker designers as well as researchers in this arena.