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Identification of public concerns about radiation through a big data analysis of questions posted on a portal site in Korea
- Source :
- Nuclear Engineering and Technology, Vol 53, Iss 6, Pp 2046-2055 (2021)
- Publication Year :
- 2021
- Publisher :
- Elsevier BV, 2021.
-
Abstract
- This paper analyzed the primary concerns about radiation among the Korean public with a big data analysis of questions posted at the section of “Knowledge iN” on the portal site NAVER in Korea from January 2010 to August 2020. First, we extracted questions about radiation and categorized them into the three categories with TF-IDF analysis: “Medical,” “Career Counseling,” and “General Interest”. The “Medical” category includes questions about radiation diagnosis or treatment. The “Career Counseling” category includes questions about entering college and the prospect of finding jobs in radiation-related fields. The “General Interest” category includes questions about terminology and the basic knowledge of radiation or radioisotopes. Second, we extracted common questions for each category. Finally, we analyzed the temporal change in the numbers of questions for each category to confirm whether there is any correlation between radiation-related events and the number of questions. The analysis results demonstrate that major radiation-related events have little relevance to the number of questions except during March 2011.
- Subjects :
- General interest
020209 energy
Big data
02 engineering and technology
030218 nuclear medicine & medical imaging
Terminology
Korean public
03 medical and health sciences
0302 clinical medicine
Basic knowledge
0202 electrical engineering, electronic engineering, information engineering
Relevance (information retrieval)
Temporal change
Career counseling
Medical education
Radiation
business.industry
TK9001-9401
Big data analysis
Identification (information)
Nuclear Energy and Engineering
TF-IDF analysis
Concerns
Nuclear engineering. Atomic power
Psychology
business
Subjects
Details
- ISSN :
- 17385733
- Volume :
- 53
- Database :
- OpenAIRE
- Journal :
- Nuclear Engineering and Technology
- Accession number :
- edsair.doi.dedup.....f15ced343c4ac4bcc08b706412829ab1
- Full Text :
- https://doi.org/10.1016/j.net.2020.11.029