Journal of Digital Convergence (디지털융복합연구)

The Society of Digital Policy and Management (한국디지털정책학회)
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Selecting a key issue through association analysis of realtime search words

실시간 검색어 연관 분석을 통한 핵심 이슈 선정

  • 정민영 (광주여자대학교 실버케어학과)
  • Received : 2015.10.12
  • Accepted : 2015.12.20
  • Published : 2015.12.28
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Abstract

Realtime search words of typical portal sites appear every few seconds in descending order by search frequency in order to show issues increasing rapidly in interest. However, the characteristics of realtime search words reordering within too short a time cause problems that they go over the key issues of the day. This paper proposes a method for deriving a key issue through association analysis of realtime search words. The proposed method first makes scores of realtime search words depending on the ranking and the relative interest, and derives the top 10 search words through descriptive statistics for groups. Then, it extracts association rules depending on 'support' and 'confidence', and chooses the key issue based on the results as a graph visualizing them. The results of experiments show that the key issue through association rules is more meaningful than the first realtime search word.

포털 사이트의 실시간 검색어는 현재 관심이 급상승하고 있는 이슈를 보여주기 위해 주로 검색횟수가 많은 순서에 따라 몇 초 간격으로 제공되고 있다. 그렇지만 너무 짧은 시간 내에 순위가 바뀌는 실시간 검색어의 특성 때문에 하루의 핵심 이슈를 비켜가는 문제가 발생한다. 본 논문에서 이러한 문제를 보완하기 위해 검색어들 사이의 연관 분석을 통하여 검색어들이 관련된 핵심 이슈를 도출하는 방법을 제안하고자 한다. 이를 위해 먼저 실시간 검색어를 순위와 상대적 관심도를 기반으로 점수화하여 집단별 기술통계를 통해 최상위 10개의 검색어를 도출한다. 그 다음으로 지지도와 신뢰도를 기반으로 연관 규칙을 추출하고 이를 가시화하는 그래프 결과를 바탕으로 핵심 이슈를 선정한다. 실험 결과는 단일 최상위 실시간 검색어보다 연관분석을 통해 높은 점수로 선정된 핵심 이슈가 더 큰 의미를 갖는다는 것을 보여준다.

Keywords

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