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Extracting Collective Trends from Twitter Using Social-Based Data Mining

  • Gema Bello
  • Héctor Menéndez
  • Shintaro Okazaki
  • David Camacho
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8083)

Abstract

Social Networks have become an important environment for Collective Trends extraction. The interactions amongst users provide information of their preferences and relationships. This information can be used to measure the influence of ideas, or opinions, and how they are spread within the Network. Currently, one of the most relevant and popular Social Network is Twitter. This Social Network was created to share comments and opinions. The information provided by users is specially useful in different fields and research areas such as marketing. This data is presented as short text strings containing different ideas expressed by real people. With this representation, different Data Mining and Text Mining techniques (such as classification and clustering) might be used for knowledge extraction trying to distinguish the meaning of the opinions. This work is focused on the analysis about how these techniques can interpret these opinions within the Social Network using information related to IKEA® company.

Keywords

Collective Trends Social Network Data Mining Classification Clustering Twitter 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Gema Bello
    • 1
  • Héctor Menéndez
    • 1
  • Shintaro Okazaki
    • 2
  • David Camacho
    • 1
  1. 1.Departamento de Ingeniería Informática. Escuela Politécnica SuperiorUniversidad Autónoma de MadridMadridSpain
  2. 2.Department of Finance and Marketing Research. College of Economics and Business AdministrationUniversidad Autónoma de MadridMadridSpain

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