Predicting the Popularity of Social Curation

Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 326)

Abstract

The amount and variety of social media content such as status, images, movies, and music are increasing rapidly. Accordingly, the social curation service is emerging as a new way to connect, select, and organize information on a massive scale. One noticeable feature of social curation services is that they are loosely supervised: the content that users create in the service is manually collected, selected, and maintained. A large proportion of these contents are arbitrarily created by inexperienced users. In this paper, we look into social curation, particularly, the Storify website1. This is the most popular social curation for creating stories included in various domains such as Twitter, Flicker, and YouTube.We propose a machine learning method with feature extraction to filter these contents and to predict the popularity of social curation data.

Keywords

curation social curation social network service prediction popularity 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Binh Thanh Kieu
    • 1
  • Ryutaro Ichise
    • 2
  • Son Bao Pham
    • 1
  1. 1.Faculty of Information Technology, University of Engineering and TechnologyVietnam National UniversityHanoiVietnam
  2. 2.National Institute of InformaticsTokyoJapan

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