• DocumentCode
    174459
  • Title

    Collaborative discovery of Chinese neologisms in social media

  • Author

    Shek Lung Lai ; Ng, Vincent Ty

  • Author_Institution
    Dept. of Comput., Hong Kong Polytech. Univ., Hong Kong, China
  • fYear
    2014
  • fDate
    5-8 Oct. 2014
  • Firstpage
    4107
  • Lastpage
    4112
  • Abstract
    The emergence of neologism in social media has bought the researchers´ attention. Traditional ways of text mining are not sufficient to handle the unique properties of messages in the new media. New methods have been developed to extract neologisms in order to help researchers to understand about community behavior in different media. In this paper, we propose a collaborative framework to detect neologisms from various social media. There are 4 different types of agents working collaboratively. Among them, the summarizing agent is using the life span parameter to confirm if an unknown character pattern is a neologism. Preliminary experiments have been performed to investigate the possible popularity patterns of some known neologisms.
  • Keywords
    data mining; natural language processing; social networking (online); collaborative Chinese neologism discovery; collaborative agents; community behavior; life span parameter; neologism detection; neologism extraction; social media; summarizing agent; unknown character pattern; Cleaning; Collaboration; Databases; Facebook; Market research; Media; Time-frequency analysis; neologism discovery; social media analysis; text mining;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man and Cybernetics (SMC), 2014 IEEE International Conference on
  • Conference_Location
    San Diego, CA
  • Type

    conf

  • DOI
    10.1109/SMC.2014.6974578
  • Filename
    6974578