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Social User Mining: Survey on Mining Different Types of Social Media Data

Author

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  • Mohammed Eltaher

    (Department of Computer Science and Engineering, University of Bridgeport, Bridgeport, CT, USA)

  • Jeongkyu Lee

    (Department of Computer Science and Engineering, University of Bridgeport, Bridgeport, CT, USA)

Abstract

In recent years, the pervasive use of social media has generated huge amounts of data that starts to gain a lot of attentions. Each social media source utilizes different data types such as textual and visual. For example, Twitter1 is for a short text message, Flickr2 is for images and videos, and Facebook3 allows all of these data types. It is highly desired to find patterns of social media users from such different data formats. With the use of data mining techniques, the social media data opens a lot of opportunities for researchers. Despite of its short history, social media mining has become very active research area. This paper provides a comprehensive survey on recent research on social user mining. In particular, the survey focuses on two aspects: (1) social user mining based on data types, such as textual, visual, and both textual and visual information, and (2) social user mining based on mining techniques. In addition, we present our current research on social user mining as well as its future directions.

Suggested Citation

  • Mohammed Eltaher & Jeongkyu Lee, 2013. "Social User Mining: Survey on Mining Different Types of Social Media Data," International Journal of Multimedia Data Engineering and Management (IJMDEM), IGI Global, vol. 4(4), pages 58-70, October.
    • Handle: RePEc:igg:jmdem0:v:4:y:2013:i:4:p:58-70
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