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A Study on Political Attitude Estimation of Korean OSN Users

온라인 소셜네트워크를 통한 한국인의 정치성향 예측 기법의 연구

  • Received : 2016.08.15
  • Accepted : 2016.08.31
  • Published : 2016.08.31

Abstract

Recently numerous studies are conducted to estimate the human personality from the online social activities. This paper develops a comprehensive model for political attitude estimation leveraging the Facebook Like information of the users. We designed a Facebook Crawler that efficiently collects data overcoming the difficulties in crawling Ajax enabled Facebook pages. We show that the category level selection can reduce the data analysis complexity utilizing the sparsity of the huge like-attitude matrix. In the Korean Facebook users' context, only 28 criteria (3% of the total) can estimate the political polarity of the user with high accuracy (AUC of 0.82).

본 연구는 Facebook 사용자들의 Like활동 정보를 사용하여 정치성향을 예측하기 위한 분석 모델과 프로그램를 개발하였다. Facebook의 Ajax사용 특성 을 반영한 Facebook 크로울러를 개발하였으며, 이를 사용하여 수집된 성기고 방대한 데이터의 상관 매트릭스 정보를 효과적의 축소하기 위한 카테고리 레벨 필터링 기법을 개발하였다. 대한민국 사용자들을 대상으로 LCA (Latent class analysis) 분석한 결과 28 개의 기준 (전체 대상페이지의 3% 미만) 으로 사용자의 정치적인 극성을 상당히 정확하게 (AUC of 0.82) 예측할 수 있음을 확인하였다.

Keywords

References

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