Journal of Internet Computing and Services (인터넷정보학회논문지)

Korean Society for Internet Information (한국인터넷정보학회)
권호 표지
DOI QR코드

DOI QR Code

A Design of Analysis System on TV Advertising Effect of Social Networking Using Hadoop

하둡을 이용한 소셜네트워킹의 TV광고효과 분석 시스템 설계

  • Hur, Seoyeon (Dept. of Computer Science, Sookmyung Women's Univ.) ;
  • Kim, Yoonhee (Dept. of Computer Science, Sookmyung Women's Univ.)
  • Received : 2013.08.01
  • Accepted : 20131131
  • Published : 2013.12.31
Download PDF
⟨ Previous Next ⟩

Abstract

As 'Big data' has been one of challenging issues, development of new services using Social Network Service (SNS) which is its typical example became active. SNS has developed as a media where everyone communicates at real time and the number of SNS opinion analyzing services is increasing. Meanwhile, new approach to acquire and analyze twitter data becomes necessary in TV advertisement system. This paper proposes LiveAD system, which store and analyze big data such as twitter data as well as analyze TV advertising effect based on twitter data. As a proof of concept, the proposed system has been implemented collecting and analyzing twitter data using Hadoop. The result of collected information over the system increases the chance of analyzing TV advertising effect on twitter in real-time.

빅데이터가 화두가 되면서, 그 대표적인 예인 SNS을 이용한 서비스 개발도 활기를 띠고 있다. SNS는 기존 매체와는 다르게 실시간으로 의견을주고받는 하나의 장으로 확장되었고, 다양하고 많은 개인들의 의견을 분석하고자 하는 서비스들도 늘어나고 있다. 한편, 매체가 다양화되면서, TV광고계에서도 광고에 대한 의견의 확보와 분석에 새로운 접근방법이 필요해졌다. 이에 본 연구에서는 TV광고의 효과를 트위터 데이터를 기반으로 분석하며 특히 하둡을 이용하여 트위터 데이터와 같은 빅데이터를 저장 및 분석하도록 하는 LiveAD라는 시스템을 설계 및 구축하여, 트위터를 대상으로 TV광고 분석을 빠르게 수행할 수 있음을 보여주었다.

Keywords

References

  1. Jin-Hyung Lee, "Trend and Expantion of SNS", http://www.kca.kr/open_content/bbs.do?act=file&bcd=radiotrends&msg_no=10462&file_no=1].
  2. ZDNet Korea, "7-years-Twitter ...Everydy-Twits 400 million", http://www.zdnet.co.kr/news/news_view.asp?artice_id=20130321205519
  3. You-Jae Lee,"Measurement of Advertising Effect", http://youjae.com/data/cdata3/20/ad13.pdf
  4. Naver encyclopedia, "Measuring Advertising Effect", http://terms.naver.com/entry.nhn?cid=512&docId=51147&mobile&categoryId=512
  5. Joseph Raymond Roy, "Burke Test", Marketing Metrics Made Simple, http://www.marketing-metricsmade-simple.com/burke-test.html
  6. AC Nielsen Media research, "Analysis of Public TV Advertising Effect and its Factor", KOBACO, 2002.04, http://www.kobaco.co.kr/information/adinfo/UploadFile/0204_132.pdf
  7. Jun-Cheon Jang, "CPRP based on Viewer Ratings has Limits to Measurement of Engagement of Viewers", KOBACO, 2009.01, http://www.kobaco.co.kr/information/adinfo/html/200901/054_%BA%D2%C8%B2%B1%E2TV.htm
  8. Ji-Hoon Song, Si-Jin Lee, Dong-Hyo Park, "Twitter message analysis system design using Hadoop", A proceedings of Korean Society for Internet Information 2012 Summer Conference, p.169-170, 2012.6.
  9. TVCF, a Web site which provide TV advertisement information, http://www.tvcf.co.kr/.
  10. Jericho HTML Parser, http://jericho.htmlparser.net/docs/index.html
  11. HighChart, http://www.highcharts.com/

Cited by

  1. 도로 침수영역의 탐색을 위한 빅데이터 분석 시스템 연구 vol.18, pp.8, 2015, https://doi.org/10.9717/kmms.2015.18.8.925