Difference between revisions of "Rao, D., D. Yarowsky, A. Shreevats, and M. Gupta. 2010. Classifying latent user attributes in twitter. In Proceedings of the 2nd international workshop on Search and mining user-generated contents, 37–44."
From Cohen Courses
Jump to navigationJump to search (Created page with '== Online Version == An online version of this [[Category::paper]] is available here: [http://www.cs.jhu.edu/~delip/smuc.pdf] == Summary == The authors investigate the use of ri…') |
(No difference)
|
Revision as of 22:26, 31 March 2011
Online Version
An online version of this paper is available here: [1]
Summary
The authors investigate the use of rich feature sets and stacked SVM based classifiers to classify latent user attributes, including gender, age, regional origin, and political orientation solely from Twitter user language.
