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.

Original languageEnglish (US)
Title of host publicationMining Text Data
PublisherSpringer US
Pages385-414
Number of pages30
Volume9781461432234
ISBN (Print)9781461432234, 1461432227, 9781461432227
DOIs
Publication statusPublished - Aug 1 2012

Keywords

  • Collaborative question answering
  • Event detection
  • Semantic knowledge
  • Short text
  • Social media
  • Social tagging
  • Text analytics
  • Text representation
  • Time sensitivity

ASJC Scopus subject areas

  • Computer Science(all)

Cite this

Hu, X., & Liu, H. (2012). Text analytics in social media. In Mining Text Data (Vol. 9781461432234, pp. 385-414). Springer US. https://doi.org/10.1007/978-1-4614-3223-4_12