Abstract

So far we have discussed the collection and management of a large set of Tweets. It is time to put these Tweets to work to gain information about the data we have collected. This chapter focuses on two key aspects of Twitter data for data analysis: networks and text.

Original languageEnglish (US)
Title of host publicationSpringerBriefs in Computer Science
PublisherSpringer
Pages35-48
Number of pages14
Edition9781461493716
DOIs
StatePublished - Jan 1 2014

Publication series

NameSpringerBriefs in Computer Science
Number9781461493716
ISSN (Print)2191-5768
ISSN (Electronic)2191-5776

Keywords

  • Eigenvector centrality
  • Latent dirichlet allocation
  • Network construction
  • Sentiment analysis
  • Topic modeling

ASJC Scopus subject areas

  • Computer Science(all)

Cite this

Kumar, S., Morstatter, F., & Liu, H. (2014). Analyzing twitter data. In SpringerBriefs in Computer Science (9781461493716 ed., pp. 35-48). (SpringerBriefs in Computer Science; No. 9781461493716). Springer. https://doi.org/10.1007/978-1-4614-9372-3_4