• 제목/요약/키워드: Concor Analysis

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Analysis on Types of Golf Tourism After COVID-19 by using Big Data

  • Hyun Seok Kim;Munyeong Yun;Gi-Hwan Ryu
    • International Journal of Advanced Culture Technology
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    • 제12권1호
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    • pp.270-275
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    • 2024
  • Introduction. In this study, purpose is to analize the types of golf tourism, inbound or outbound, by using big data and see how movement of industry is being changed and what changes have been made during and after Covid-19 in golf industry. Method Using Textom, a big data analysis tool, "golf tourism" and "Covid-19" were selected as keywords, and search frequency information of Naver and Daum was collected for a year from 1 st January, 2023 to 31st December, 2023, and data preprocessing was conducted based on this. For the suitability of the study and more accurate data, data not related to "golf tourism" 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, top 36 keywords with the highest relevance and search frequency were selected and applied to this study. The top 36 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. Results By using big data analysis, it was found out option of oversea golf tourism is affecting on inbound golf travel. "Golf", "Tourism", "Vietnam", "Thailand" showed high frequencies, which proves that oversea golf tour is now the re-coming trends.

사회-공간 네트워크 분석을 활용한 초등학교 공간계획방향에 관한 연구 (A Study on Improvement of the School Space through Socio-Spatial Network Analysis)

  • 전영훈;김윤영
    • 대한건축학회논문집:계획계
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    • 제35권5호
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    • pp.21-30
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    • 2019
  • The purpose of this study is to present the direction of the new space plan by reflecting the opinions of the user (student) in the existing standardized elementary school space planning. The purpose of this study is to investigate the activities of elementary school students by using socio - spatial network analysis method and to propose the direction of new elementary school space planning through the results. We analyzed the results of each centrality by using the analysis of closeness analysis, betweeness analysis, girvan-newman clustering, and concor analysis. The results of this study are as follows. First, it should be planned to use the classroom and the special room as one area by utilizing the corridor. Second, it should be planned that the outdoor space and the indoor space are closely related to each other by utilizing the hall, the lobby and the classroom. Third, the school should create a small space where physical activity is possible in an indoor space of the school. In order to improve the standardized elementary school space, this study proposes a method to reflect the opinions of the users in the school planning stage.

Analysis of Covid-19, Tourism, Stress Keywords Using Social Network Big Data_Semantic Network Analysis

  • Yun, Su-Hyun;Moon, Seok-Jae;Ryu, Ki-Hwan
    • International Journal of Advanced Culture Technology
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    • 제10권1호
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    • pp.204-210
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    • 2022
  • From the 1970s to the present, the number of new infectious diseases such as SARS, Ebola virus, and MERS has steadily increased. The new infectious disease, COVID-19, which began in Wuhan, Hubei Province, China, has pushed the world into a pandemic era. As a result, Countries imposed restrictions on entry to foreign countries due to concerns over the spread of COVID-19, which led to a decrease in the movement of tourists. Due to the restriction of travel, keywords such as "Corona blue" have soared and depression has increased. Therefore, this study aims to analyze the stress meaning network of the COVID-19 era to derive keywords and come up with a plan for a travel-related platform of the Post-COVID 19 era. This study conducted analysis of travel and stress caused by COVID-19 using TEXTOM, a big data analysis tool, and conducted semantic network analysis using UCINET6. We also conducted a CONCOR analysis to classify keywords for clustering of words with similarities. However, since we have collected travel and stress-oriented data from the start to the present, we need to increase the number of analysis data and analyze more data in the future.

빅데이터 분석을 통한 한국과 미국의 스타벅스 비교 분석 (A Comparison of Starbucks between South Korea and U.S.A. through Big Data Analysis)

  • 조아라;김학선
    • 한국조리학회지
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    • 제23권8호
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    • pp.195-205
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    • 2017
  • The purpose of this study was to compare the Starbucks in South Korea with Starbucks in U.S.A through the semantic network analysis of big data by collecting online data with SCTM(Smart Crawling & Text Mining) program which was developed by big data research institute at Kyungsung University, a data collecting and processing program. The data collection period was from January 1st 2014 to December 7th 2017, and packaged Netdraw along with UCINET 6.0 were utilized for data analysis and visualization. After performing CONCOR(convergence of iterated correlation) analysis and centrality analysis, this study illustrated the current characteristics of Starbucks for Korea and U.S.A reflected by the social network and the differences between Korea and U.S.A. Since the Starbucks was greatly developed, especially in Korea. this study also was supposed to provide significant and social-network oriented suggestions for Starbucks USA, Starbucks Korea and also the whole coffee industry. Also this study revealed that big data analytics can generate new insights into variables that have been extensively studied in existing hospitality literature. In addition, implications for theory and practice as well as directions for future research are discussed.

A Study on the Analysis of Museum Gamification Keywords Using Social Media Big Data

  • Jeon, Se-won;Choi, YounHee;Moon, Seok-Jae;Yoo, Kyung-Mi;Ryu, Gi-Hwan
    • International Journal of Internet, Broadcasting and Communication
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    • 제13권4호
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    • pp.66-71
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    • 2021
  • The purpose of this paper is to identify keywords related to museums, gamification, and visitors, and provide basic data that the museum market can be expanded by using gamification. That used to collect data for blogs, news, cafes, intellectuals, academic information by Naver and Daum which is Web documents in Korea, and Google Web, news, Facebook, Baidu, YouTube, and Twitter for analysis. For the data analysis period, a total of one year of data was selected from April 16, 2020 to April 16, 2021, after Corona. For data collection and analysis, the frequency and matrix of keywords were extracted through Textom, a social matrix site, and the relationship and connection centrality between keywords were analysed and visualized using the Netdraw function in the UCINET6 program. In addition, We performed CONCOR analysis to derive clusters for similar keywords. As a result, a total of 25,761 cases that analysing the keywords of museum, gamification and visitors were derived. This shows that the museum, gamification, and spectators are related to each other. Furthermore, if a system using gamification is developed for museums, the museum market can be developed.

A Study on the Promotion of Yakseon Food Using Big Data

  • LEE, JINHO;KIM, AE SOOK;Hwang, Chi-Gon;Ryu, Gi Hwan
    • International Journal of Internet, Broadcasting and Communication
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    • 제14권4호
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    • pp.41-46
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    • 2022
  • The purpose of this study is to confirm and analyze the impact on consumers through big data keyword analysis on weak food. For data collection, web documents, blogs, news, cafes, intellectuals, academic information, and Google Web, news, and Facebook provided by Naver and Daum were used as analysis targets. The data analysis period was set from January 2018 to December 2021. For data collection and analysis, the frequency and matrix of keywords were extracted through Textom, a social matrix site, and the relationship and connection centrality between keywords were analyzed and visualized using the Netdraw function among UCINET6 programs. In addition, CONCOR analysis was conducted to derive clusters for similar keywords. As a result of analyzing yakseon food with keywords, a total of 35,985 cases of collected data were derived. Through this, it was confirmed that medicinal food affects consumers. Furthermore, if a business model is created and developed through yakseon food, it will be possible to lead the popularization of yakseon food.

A Study on Social Perceptions of Public Libraries Utilizing the sentiment analysis

  • Noh, Younghee;Kim, Dongseok
    • International Journal of Knowledge Content Development & Technology
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    • 제12권4호
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    • pp.41-65
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    • 2022
  • This study would understand the overall perception of our society about public libraries, analyzing the texts related to public libraries, utilizing the semantic connection network & sentiment analysis. For this purpose, this study collected data from the last five years with keywords, 'Library' and 'Lifelong Learning Center' from January 1, 2016 through November 30, 2020 through the blogs and cafés of major domestic portal sites. With the collected data, text mining, centrality of keywords, network structure, structural equipotentiality, and sensitivity analyses were conducted. As a result of the analysis, First, 'reading' and 'book' were identified as representative keywords that form the social perception of public libraries. Second, it turned out that there were keywords related to the use of the library and the untact service due to the recent spread of COVID-19. Third, in seeking a plan for the development of public libraries through the keywords drawn to have positive meanings, it is necessary to create continuous services that can form a new image of the library, breaking away from the existing fixed role and image of the library and increase the convenience of use. Fourth, facilities and facilities for library services were recognized from a neutral point of view. Fifth, the spread of infectious diseases, social distancing, and temporary closure and closure of libraries are negatively related to public libraries, and awareness of librarians has been identified as negative keywords.

언어 네트워크 분석을 통한 노인 구강 건강 연구 동향 탐구 (Exploring the research trends of elderly oral health through language network analysis)

  • 김윤정
    • 한국치위생학회지
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    • 제23권6호
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    • pp.451-458
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    • 2023
  • Objectives: The purpose of this study is to explore the research trends of elderly oral health through a language network analysis. Methods: A total of 354 published studies with 668 keywords were collected from the Research Information Sharing Service (RISS) between 2000 and 2022. Language network analysis was performed using Textom 6.0, Ucinet 6.774, and NetDraw 2.183. Results: The most frequent keywords were 'elderly', 'oral health', 'quality of life', and 'OHIP-14'. The result of frequency-inverse document frequent keywords showed similar results to the most frequent keywords. The N-gram of keywords shows that 'elderly', 'oral health' (18 times) and 'elderly', 'depression' (7 times). As a results of the analysis of degree centrality and between centrality, 'elderly', 'oral health', and 'quality of life' were found to be high. The CONCOR analysis identified the main clusters of 'quality of life', 'oral health behavior', 'health', and 'oral function disorder'. Conclusions: The results of the current study could be available to know research trends in elderly oral health and it is necessary to improve more comprehensive study in follow-up study.

A Study of Comparison between Cruise Tours in China and U.S.A through Big Data Analytics

  • Shuting, Tao;Kim, Hak-Seon
    • 한국조리학회지
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    • 제23권6호
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    • pp.1-11
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    • 2017
  • The purpose of this study was to compare the cruise tours between China and U.S.A. through the semantic network analysis of big data by collecting online data with SCTM (Smart crawling & Text mining), a data collecting and processing program. The data analysis period was from January $1^{st}$, 2015 to August $15^{th}$, 2017, meanwhile, "cruise tour, china", "cruise tour, usa" were conducted to be as keywords to collet related data and packaged Netdraw along with UCINET 6.0 were utilized for data analysis. Currently, Chinese cruisers concern on the cruising destinations while American cruisers pay more attention on the onboard experience and cruising expenditure. After performing CONCOR (convergence of iterated correlation) analysis, for Chinese cruise tour, there were three clusters created with domestic destinations, international destinations and hospitality tourism. As for American cruise tour, four groups have been segmented with cruise expenditure, onboard experience, cruise brand and destinations. Since the cruise tourism of America was greatly developed, this study also was supposed to provide significant and social network-oriented suggestions for Chinese cruise tourism.

코로나19 관련 키워드 분석: 토픽 모델링과 의미 연결망 네트워크 분석을 중심으로 (COVID19 Related Keyword Analysis: Based on Topic Modeling and Semantic Network Analysis)

  • 김동욱;이민상;정재영;김현철
    • 반도체디스플레이기술학회지
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    • 제21권2호
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    • pp.127-132
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    • 2022
  • In the era of COVID-19 pandemic, COVID related keywords, news and SNS data are pouring out. With the help of the data and LDA topic modeling, we can check out what media reports about COVID-19 and vaccines. Also, we can be clear how the public reacts to the vaccine on social media and how this is related with the increasing number of COVID-19 patients. By using sentimental analysis methodology, we can get to know about the different kinds of reports that Korea media send out and get to know what kind of emotions that each media company uses in majority. Through this procedure, we can know the difference between the Korean media and the foreign ones. Ultimately, we can find and analyze the keyword that suddenly rose during the COVID-19 period throughout this research.