Predicting an Author's Demographics from Text using Topic Modeling Approach

@inproceedings{Iqbal2015PredictingAA,
  title={Predicting an Author's Demographics from Text using Topic Modeling Approach},
  author={Hafiz Rizwan Iqbal and Muhammad Adnan Ashraf and Rao Muhammad Adeel Nawab},
  booktitle={CLEF},
  year={2015}
}
The paper presents an approach to predict personality traits of a writer for the author profiling task of the PAN CLEF 2015. The task aimed at predicting authors’ demographics based on the written tweets of an author. These demographics included traditional authorship attributes of age, gender and various personality traits of an author. We applied topic modeling using LDA as baseline approach and used the generated topic to get hierarchical probabilities of the topics. J48 decision tree was… CONTINUE READING

From This Paper

Figures, tables, and topics from this paper.

References

Publications referenced by this paper.
Showing 1-10 of 11 references

MALLET: A Machine Learning for Language Toolkit

  • McCallum, Andrew Kachites.
  • http://mallet.cs.umass.edu
  • 2002
Highly Influential
4 Excerpts

Overview of the 3rd author profiling task at pan 2015

  • F. Rangel, P. Rosso, M. Potthast, B. Stein, W. Daelemans
  • Cappellato L., Ferro N., Gareth J. and San Juan E…
  • 2015
1 Excerpt

A Simple Approach to Author Profiling in MapReduce, Notebook for PAN, CLEF

  • M. Suraj, S. Prasha, S. Thamar
  • 2014
1 Excerpt

Jordan , Michael I . : Latent Dirichlet allocation

  • Andrew Y. Ng
  • Laffer - ty , John . Journal of Machine Learning…
  • 2014

Similar Papers

Loading similar papers…