• DocumentCode
    682450
  • Title

    Knowledge discovery in hashtags#

  • Author

    Mehmood, Rashid ; Maurer, Helmut ; Afzal, Muhammad Tanvir

  • Author_Institution
    Inst. for Inf. Syst. & Comput. Media, Graz Univ. of Technol., Graz, Austria
  • fYear
    2013
  • fDate
    9-10 Dec. 2013
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Twitter is a breed of social networks that are playing a buoyant role in today\´s world communication. This paper is an attempt to apply knowledge discovery process on Twitter dataset comprising hashtags along with the visual analytic techniques whose purpose is to provide information to the people in such a way so that they understand concealed knowledge in the data effortlessly and meritoriously. We further analyze tweet text and metadata associated with each tweet for identification of useful patterns like "who talks to whom" and "how much". Our research reveals the impact of visualization and hierarchical clustering technique in analyzing similar groups of users. Further we investigate different social network measures that unveil the influence of users in the particular hashtags.
  • Keywords
    data mining; data visualisation; meta data; pattern clustering; social networking (online); text analysis; Twitter; hashtags#; hierarchical clustering technique; knowledge discovery; metadata analysis; social networks; tweet text analysis; visual analytic techniques; visualization technique; Communities; Data mining; Data visualization; Knowledge discovery; Libraries; Twitter; Data mining; Database; NLP; Social Network Analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Emerging Technologies (ICET), 2013 IEEE 9th International Conference on
  • Conference_Location
    Islamabad
  • Print_ISBN
    978-1-4799-3456-0
  • Type

    conf

  • DOI
    10.1109/ICET.2013.6743538
  • Filename
    6743538