KIISE Transactions on Computing Practices (정보과학회 컴퓨팅의 실제 논문지)

Korean Institute of Information Scientists and Engineers (한국정보과학회)
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A Design of a TV Advertisement Effectiveness Analysis System Using SNS Big-data

SNS Big-data를 활용한 TV 광고 효과 분석 시스템 설계

  • 이아름 (숙명여자대학교 컴퓨터과학부) ;
  • 방지선 (숙명여자대학교 컴퓨터과학부) ;
  • 김윤희 (숙명여자대학교 컴퓨터과학부)
  • Received : 2014.11.13
  • Accepted : 2015.06.16
  • Published : 2015.09.15
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Abstract

As smart-phone usage increases, the number of Social Networking Service (SNS) users has also exponentially increased. SNS allows people to efficiently exchange their personal opinion, and for this reason, it is possible to collect the reaction of each individual to a given event in real-time. Nevertheless, new methods need to be developed to collect and analyze people's opinion in real-time in order to effectively evaluate the impact of a TV advertisement. Hence, we designed and constructed a system that analyzes the effect of an advertisement in real-time by using data related to the advertisement collected from SNS, specifically, Twitter. In detail, Hadoop is used in the system to enable big-data analysis in parallel, and various analyses can be conducted by conducting separate numerical analyses of the degrees of mentioning, preference and reliability. The analysis can be accurate if the reliability is assessed using opinion mining technology. The proposed system is therefore proven to effectively handle and analyze data responses to divers TV advertisement.

스마트폰 보급률이 증가함과 함께 SNS(Social Networking Service) 이용자도 늘어가고 있다. SNS는 실시간으로 사람들 간의 개인적인 의견을 빠르게 주고받을 수 있다는 특징이 있어 이를 통해 개인의 반응을 실시간으로 수집, 분석이 가능하다. 한편, TV광고 효과 분석에 있어 사람들의 의견을 실시간으로 수집하고 분석하기 위해 새로운 접근 방법이 필요해졌다. 이에 본 연구에서는 트위터라는 특정 SNS를 대상으로 광고에 대한 데이터를 수집하여 실시간으로 광고 효과를 분석하는 시스템을 설계 및 구축하였다. 특히, 하둡을 이용하여 빅데이터 분석을 병렬화하여 효율적으로 수행하도록 하였으며, TV광고에 대해 언급도와 선호도, 신뢰도를 각각 분석하여 다양한 분석을 가능하게 하였다. 오피니언 마이닝 기법을 신뢰도 분석에 사용하여 분석의 정확도를 높였다. 구축한 시스템을 통해 트위터 SNS를 대상으로 TV광고에 대한 분석을 세분화하여 신속하게 처리할 수 있음을 보여주었다.

Keywords

Acknowledgement

Supported by : 숙명여자대학교

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