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TKG: A Graph-Based Approach to Extract Keywords from Tweets

  • Willyan Daniel AbilhoaEmail author
  • Leandro Nunes de Castro
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 290)

Abstract

Twitter is a microblog service that generates a huge amount of textual content daily. All this content needs to be explored by means of text mining, natural language processing, information retrieval, and other techniques. In this context, automatic keyword extraction is a task of great usefulness. A fundamental step in text mining techniques consists of building a model for text representation. This paper proposes a keyword extraction method for tweet collections that represents texts as graphs and applies centrality measures for finding the relevant vertices (keywords). The proposal is applied to two tweet collections of Brazilian TV shows and its results are compared to those of TFIDF and KEA.

Keywords

Knowledge Discovery Text Mining Keyword Extraction Graph Theory Centrality Measures 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Willyan Daniel Abilhoa
    • 1
    Email author
  • Leandro Nunes de Castro
    • 1
  1. 1.Natural Computing LaboratoryMackenzie Presbyterian UniversitySão PauloBrazil

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