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Research Trend Analysis on Big Data through Topic Modeling and Semantic Network Analysis
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토픽 모델링과 의미연결망 분석을 통한 빅데이터 연구동향 분석

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Type
Academic journal
Author
Hye-Jin Kwon (경성대학교) Hak-Seon Kim (경성대학교)
Journal
Culinary Society of Korea Culinary Science & Hospitality Research Vol.27 No.3(Wn.128) KCI Accredited Journals
Published
2021.3
Pages
1 - 14 (14page)

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Research Trend Analysis on Big Data through Topic Modeling and Semantic Network Analysis
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Big data is a concept formed during the Fourth Industrial Revolution and is based on highly advanced information and communication technologies including artificial intelligence and the internet of things. The use of vast amounts of big data generated by convergence with other industries emerging as a very important challenge in this time. This study aimed at understanding trends of big data studies and deriving implications for directions of the studies by utilizing text mining. For this purpose, this study included topic modeling and semantic network analysis based between January 1, 2016 and December 31, 2020, investigated in ordet to examine various characteristics and development of big data studies. As a topic modeling and semantic network analysis tool, NetMiner 4.4.3.e program, which is widely used in social network analysis, was used. The findings of the study show that big data related studies has been steadily increasing, and big data has been actively conducted mainly on technical methods. 9 topics related to protection of personal information, analyze consumer factor, analysis of healthcare and children education by group, utilize system processing and information, topic and network analysis in education, regional tourism image analysis, semantic network analysis using key word, policy analysis technology in the industrial field and analysis news articles key word were created.
#Big data #Text mining #Topic modeling #Semantic network analysis #Word cloud

Contents

ABSTRACT
1. 서론
2. 이론적 배경
3. 연구방법
4. 분석결과
5. 결론
REFERENCES

References (45)

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Ban, H. J., & Kim, H. S. (2019). A study on the review analysis of restaurant recognition in busan 2: Especially concerning Korean reviews. The Journal of Business Economics, 35(2), 185-207. google schola Ban, H. J., & Jun, J. K. (2019). A study on the semantic network analysis of luxury hotel and business hotel through the big data. Culinary Science & Hospitality Research, 25(1), 18-28. google schola Ban, H. J., & Kim, H. D., & Kim, H. S. (2020). A study on the experience of casino hotel using online review analysis. Culinary Science & Hospitality Research, 26(7), 22-29. google schola Blei, D. M. (2012). Probabilistic topic models. Communications of the ACM, 55(4), 77-84. google schola Bonacich, P. (1972). Factoring and weighting approaches to status scores and clique identification. Journal of Mathematical Sociology, 2(1), 113-120. google schola

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