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Facebook Fan Page Evaluation System Based on User Opinion Mining

오피니언 마이닝을 이용한 페이스북 팬 페이지 평가 시스템

  • Received : 2015.12.07
  • Accepted : 2015.12.15
  • Published : 2015.12.30

Abstract

In this paper, we propose the Facebook fan page evaluation system, which evaluates user opinions based on lexicon-based analysis and positive/negative response from users. By comparing the performance with existing evaluation systems, it is verified that the proposed system can evaluate the fan page in more accurate way.

본 논문에서는 페이스북에 게시된 글의 어휘 분석 및 호불호를 평가하여, 게시된 글에 대한 정확한 평가를 할 수 있는 시스템을 제안하였다. 기존 평가시 스템과의 성능 비교를 통하여 제안 시스템의 평가 정확도가 높음을 확인하였다.

Keywords

References

  1. S. Moghaddam and F. Popowich, Opinion Polarity Identification through Adjectives (2010), CoRR, Retrieved Oct. 30, 2014, from http://arxiv.org/abs/1011.4623
  2. F. A. Nielsen, AFINN word database an affective lexicon (2011), Retrieved Sept. 15, 2014, from http://www2.imm.dtu.dk/pubdb/views/edoc_download.php/6010/zip/imm6010.zip
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Cited by

  1. 협업 필터링과 빈발 패턴을 이용한 개인화된 그룹 추천 vol.41, pp.7, 2016, https://doi.org/10.7840/kics.2016.41.7.768