• DocumentCode
    3728188
  • Title

    Modelling Polarity of Articles and Identifying Influential Authors through Social Movements

  • Author

    Ming-Hung Wang;Chin-Laung Lei

  • Author_Institution
    Dept. of Electr. Eng., Nat. Taiwan Univ., Taipei, Taiwan
  • fYear
    2015
  • Firstpage
    1664
  • Lastpage
    1669
  • Abstract
    Sunflower Movement is one of the most influential social movements in Taiwan over the past few decades. In order to protest the review process at the legislature, the protesters entered and occupied the building of the Legislative Yuan (the parliament) of Taiwan on March 18, 2014, without any sign in advance. This action shook the government and caught a high level of attention in Taiwan. People discussed the action from different viewpoints and showed their supporting and opposition on the movement in daily life as well as on social media sites. However, the information is in chaos since a large number of articles had been published during the movement. In order to realize the social discussions in a comprehensive way, major issues such as extracting notable threads and finding important authors among social sites need to be addressed. In this paper, we provide methodologies to quantify and predict the polarity of each article, we also present a consensus-based approach to identify influential authors on the social forum. From our results, our proposal is effective and efficient for identifying information and authors that are worthy of attention through the social movement.
  • Keywords
    "Proposals","Social network services","Government","Media","Data mining","Peer-to-peer computing","Predictive models"
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics (SMC), 2015 IEEE International Conference on
  • Type

    conf

  • DOI
    10.1109/SMC.2015.293
  • Filename
    7379425