정보과학회 논문지 (Journal of KIISE)

  • 제41권12호
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  • Pages.1136-1144
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  • 2014
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  • 2383-630X(pISSN)
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  • 2383-6296(eISSN)
한국정보과학회 (Korean Institute of Information Scientists and Engineers)
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트위터 특징에 기반한 콘텐츠 중요성 평가 기법

An Evaluation Method for Contents Importance Based on Twitter Characteristics

  • 이의종 (고려대학교 컴퓨터전파통신공학) ;
  • 김정동 (고려대학교 컴퓨터전파통신공학) ;
  • 백두권 (고려대학교 융합소프트웨어 전문대학원)
  • 투고 : 2014.02.20
  • 심사 : 2014.10.02
  • 발행 : 2014.12.15
⟨ 이전 논문 다음 논문 ⟩

초록

트위터는 하루 약 1억 4000만개의 콘텐츠를 생성하는 소셜 네트워크 서비스로 다양한 데이터를 포함하고 있으며 이를 분석하기 위한 연구가 다방면에서 진행 중에 있다. 본 연구는 트위터의 콘텐츠 검색 분야에서 유용하게 사용될 수 있는 콘텐츠 중요성을 평가하기 위한 연구이다. 트위터 콘텐츠의 중요성이란 단일 콘텐츠가 트위터 서비스 사용자들에게 사실관계가 명확한 정보를 전달하고 있는지를 평가하는 요소를 말한다. 본 논문은 트위터 콘텐츠의 중요성 평가를 위해 콘텐츠 작성자의 청자 수인 팔로워와 콘텐츠의 인기도라고 할 수 있는 리트윗을 사용했다. 더불어 실제 트위터 데이터를 사용해 제안한 방법이 효과적으로 콘텐츠의 영향력을 측정할 수 있음을 보였다. 또한 정보를 전달하는 정보 전달자의 분류를 통해 공공성을 띈 사용자의 분류가 작성한 콘텐츠가 트위터 영향력 측정에 유용하게 사용될 수 있음을 트위터 데이터 분석을 통해 보여주었다.

Twitter is a social network service that generates about 140 million contents a day. Contents of Twitter contain a variety of information and many researchers research those in various fields. In this research, we propose a method for evaluating the importance of content based on characteristics of Twitter. We have found that number of follower means user's popularity and Re-tweet that means the popularity of content. We perform experiments about proposed method using real Twitter data for proving effectiveness of proposed method. Also, we found information providers in Twitter are public user who represent a company or a representative of a specific group.

키워드

과제정보

연구 과제 주관 기관 : 한국연구재단

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피인용 문헌

  1. Geographical Name Denoising by Machine Learning of Event Detection Based on Twitter vol.4, pp.10, 2015, https://doi.org/10.3745/KTSDE.2015.4.10.447