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http://dx.doi.org/10.9723/jksiis.2022.27.5.037

Social Media Bigdata Analysis Based on Information Security Keyword Using Text Mining  

Chung, JinMyeong (경북대학교 정보보호학과)
Park, YoungHo (경북대학교 전자공학부)
Publication Information
Journal of Korea Society of Industrial Information Systems / v.27, no.5, 2022 , pp. 37-48 More about this Journal
Abstract
With development of Digital Technology, social issues are communicated through digital-based platform such as SNS and form public opinion. This study attempted to analyze big data from Twitter, a world-renowned social network service, and find out the public opinion. After collecting Twitter data based on 14 keywords for 1 year in 2021, analyzed the term-frequency and relationship among keyword documents with pearson correlation coefficient using Data-mining Technology. Furthermore, the 6 main topics that on the center of information security field in 2021 were derived through topic modeling using the LDA(Latent Dirichlet Allocation) technique. These results are expected to be used as basic data especially finding key agenda when establishing strategies for the next step related industries or establishing government policies.
Keywords
Information security; Text mining; Topic modeling; Social media;
Citations & Related Records
Times Cited By KSCI : 6  (Citation Analysis)
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