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논문검색

Technology Convergence (TC)

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

초록

영어

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.

목차

Abstract
1. INTRODUCTION
2. RELATED WORKS
3. METHOD
3.1 Analysis Target and Data Collection
3.2 Data Analysis
3.3 COVID-19, Travel, Stress Frequency Analysis
3.4 Centrality and Network Visualization of key words
3.5 CONCOR Analysis
4. CONCLUSION
REFERENCES

저자정보

  • Su-Hyun Yun Kwangwoon University, Graduate School, Seoul, Korea
  • Seok-Jae Moon Professor, Department of Artificial Intelligence, KwangWoon University, Nowon-gu, Korea
  • Ki-Hwan Ryu Professor, Department of Tourism Industry, Graduate School of Smart Convergence, Kwangwoon University, Korea

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