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Text Analytics in Social Media

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Mining Text Data

Abstract

The rapid growth of online social media in the form of collaborativelycreated content presents new opportunities and challenges to both producers and consumers of information. With the large amount of data produced by various social media services, text analytics provides an effective way to meet usres’ diverse information needs. In this chapter, we first introduce the background of traditional text analytics and the distinct aspects of textual data in social media. We next discuss the research progress of applying text analytics in social media from different perspectives, and show how to improve existing approaches to text representation in social media, using real-world examples.

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Authors and Affiliations

  1. Computer Science and Engineering, Arizona State University, Phoenix, USA

    Xia Hu & Huan Liu

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  1. Xia Hu
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  2. Huan Liu
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Correspondence to Xia Hu .

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  1. Thomas J. Watson Research Center, IBM, Skyline Drive 19, Hawthorne, 10532, New York, USA

    Charu C. Aggarwal

  2. at Urbana-Champaign, University of Illinois, URBANA, 61801, Illinois, USA

    ChengXiang Zhai

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Hu, X., Liu, H. (2012). Text Analytics in Social Media. In: Aggarwal, C., Zhai, C. (eds) Mining Text Data. Springer, Boston, MA. https://doi.org/10.1007/978-1-4614-3223-4_12

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  • DOI: https://doi.org/10.1007/978-1-4614-3223-4_12

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