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A Study on Analysis of the Trend of Blockchain by Key Words Network Analysis

키워드 네트워크 분석 방법을 활용한 블록체인 트렌드 분석에 관한 연구

  • Cho, Seong-Hwan (Department of IT Software, Division of Global Convergence, Geumgang University)
  • Received : 2018.08.31
  • Accepted : 2018.10.23
  • Published : 2018.10.30

Abstract

This study aims to identify and compare contents and keywords used in articles related to blockchain applications to various industries. The text mining and Semantic Network Analysis, as methods of keyword network analysis, were used to analyze articles including terms of 'finance' 'energy' and 'logistics', which media and government frequently mentioned as areas that can apply blockchain technologies. For this study, data were collected from 43,093 articles from January, 2017 through July, 2018. Data crawling was carried out by using Python BeautifulSoup and data cleaning was performed in order to eliminate mutual redundancies of the three terms. After that, text mining and semantic network analysis were performed using Textom and UCInet for network analysis between keywords. The results showed that all the three terms were similar in terms of 'technology', but there were differences in the contents of 'government policy' or 'industry' issues. In addition, there were differences in frequencies and centralities of these terms.

본 연구는 키워드 네트워크 분석에 사용되는 텍스트마이닝과 의미연결망 분석 방법을 활용하여 블록체인의 산업 활용 분야로 언론 및 정부 발표에서 언급되고 있는 '금융', '에너지', '물류'를 언급한 기사들을 비교 분석하였다. 블록체인 적용이 언급된 산업 분야별로 기사의 내용 및 키워드의 차이를 파악하고 비교 분석하는 것을 목적으로 하였다. 2017년 1월부터 2018년 7월까지 언론에서 보도한 총 43,093건의 기사를 Python BeautifulSoup을 이용하여 네이버 뉴스에서 수집하였고, 세 용어의 상호 중복을 제거하기 위한 정제 작업을 수행하였다. 이후 키워드 간 네트워크 분석을 위해 텍스톰(Textom)과 UCINET을 이용하여 세 용어에 대한 텍스트마이닝과 의미연결망 분석을 진행하였다. 분석 결과, 세 용어는 모두 '기술' 측면에서는 유사한 단어들이 있었으나, '정부 정책'이나 '산업'측면의 이슈 등에서 내용적 차이가 있었다. 또한 빈도 및 중심성에 있어서도 차이가 있음을 확인할 수 있었다.

Keywords

References

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