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빅데이터 시각에서 본 단일기관의 위장관 질환 블로그 분석

Other Titles
 Analysis of a Blog for Gastrointestinal Disease in the View Point of the Big Data: A Single Institutional Study 
 최정란  ;  박효진  ;  이충현 
 Korean Journal of Gastroenterology, Vol.63(6) : 361-365, 2014 
Journal Title
 Korean Journal of Gastroenterology 
Issue Date
Blogging/statistics & numerical data* ; Databases, Factual ; Dizziness/prevention & control ; Gastrointestinal Diseases/prevention & control* ; Humans ; Internet ; Metaplasia/prevention & control ; Stomach Neoplasms/prevention & control ; User-Computer Interface
Big data ; Blogging ; Metaplasia ; Gastrointestinal diseases
Background/Aims: With the enormous increase in the amount of data, the concept of big data has emerged and this allows us to gain new insights and appreciate its value. However, analysis related to gastrointestinal diseases in the viewpoint of the big data has not been performed yet in Korea. This study analyzed the data of the blog’s visitors as a set of big data to investigate questions they did not mention in the clinical situation. Methods: We analyzed the blog of a professor whose subspecialty is gastroenterology at Gangnam Severance Hospital. We assessed the changes in the number of visitors, access path of visitors, and the queries from January 2011 to December2013.Results: A total of 50,084 visitors gained accessed to the blog. An average of 1,535.3 people visited the blog per month and 49.5 people per day. The number of visitors and the cumulative number of registered posts showed a positive correlation. The most utilized access path of visitors to the website was blog.iseverance.com (42.2%), followed by Google (32.8%) and Daum (6.6%). The most searched term by the visitors in the blog was intestinal metaplasia (16.6%), followed by dizziness(8.3%) and gastric submucosal tumor (7.0%).Conclusions: Personal blog can function as a communication route for patients with digestive diseases. The most frequently searched word necessitating explanation and education was ‘intestinal metaplasia’. Identifying and analyzing even unstructured data as a set of big data is expected to provide meaningful information.
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Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Internal Medicine (내과학교실) > 1. Journal Papers
Yonsei Authors
Park, Hyo Jin(박효진) ORCID logo https://orcid.org/0000-0003-4814-8330
Choi, Jung Ran(최정란)
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