• DocumentCode
    1787461
  • Title

    Social Network Data Mining Using Natural Language Processing and Density Based Clustering

  • Author

    Khanaferov, David ; Luc, Christopher ; Taehyung Wang

  • Author_Institution
    Dept. of Comput. Sci., California State Univ., Northridge, CA, USA
  • fYear
    2014
  • fDate
    16-18 June 2014
  • Firstpage
    250
  • Lastpage
    251
  • Abstract
    There is a growing need to make sense of all the raw data available on the Internet, hence, the purpose of this study is to explore the capabilities of data mining algorithms applied to social networks. We propose a system to mine public Twitter data for information relevant to obesity and health as an initial case study. This paper details the findings of our project and critiques the use of social networks for data mining purposes.
  • Keywords
    data mining; medical administrative data processing; natural language processing; pattern clustering; social networking (online); density based clustering; health information; natural language processing; obesity information; public Twitter data mining; social network data mining; Cleaning; Clustering algorithms; Data mining; Natural language processing; Semantics; Twitter; NLP; clustering; data mining; sentiment analysis; social network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Semantic Computing (ICSC), 2014 IEEE International Conference on
  • Conference_Location
    Newport Beach, CA
  • Print_ISBN
    978-1-4799-4002-8
  • Type

    conf

  • DOI
    10.1109/ICSC.2014.48
  • Filename
    6882032