• DocumentCode
    141816
  • Title

    A hashtags dictionary from crowdsourced definitions

  • Author

    Ghenname, Merieme ; Subercaze, Julien ; Gravier, Christophe ; Laforest, Frederique ; Abik, Mounia ; Ajhoun, R.

  • Author_Institution
    LT2C, Univ. Jean Monnet, St. Etienne, France
  • fYear
    2014
  • fDate
    March 31 2014-April 4 2014
  • Firstpage
    39
  • Lastpage
    44
  • Abstract
    Hashtags are user-defined terms used on the Web to tag messages like microposts, as featured on Twitter. Because a hashtag is a textual word, its representation does not convey all the concepts it embodies. Several online dictionaries have been manually and collaboratively built to provide natural language definitions of hashtags. Unfortunately, these dictionaries in their rough form are inefficient for their inclusion in automatic text processing systems. As hashtags can be polysemic, dictionaries are also agnostic to collision of hashtags. This paper presents our approach for the automatic structuration of hashtags definitions into synonym rings. We present the output as a so-called folksionary, i.e. a single integrated dictionary built from everybody´s definitions. For this purpose, we achieved a semantic-relatedness clustering to group definitions that share the same meaning.
  • Keywords
    outsourcing; social networking (online); text analysis; Twitter; automatic text processing systems; crowdsourced definitions; folksionary; hashtags dictionary; natural language definitions; online dictionaries; semantic-relatedness clustering; synonym rings; textual word; Clustering algorithms; Context; Dictionaries; Knowledge based systems; Measurement; Natural languages; Prototypes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Engineering Workshops (ICDEW), 2014 IEEE 30th International Conference on
  • Conference_Location
    Chicago, IL
  • Type

    conf

  • DOI
    10.1109/ICDEW.2014.6818300
  • Filename
    6818300