Cross-cultural analysis of blogs and forums with mixed-collection topic models

Michael Paul, Roxana Girju

Research output: Contribution to conferencePaper

Abstract

This paper presents preliminary results on the detection of cultural differences from people's experiences in various countries from two perspectives: tourists and locals. Our approach is to develop probabilistic models that would provide a good framework for such studies. Thus, we propose here a new model, ccLDA, which extends over the Latent Dirichlet Allocation (LDA) (Blei et al., 2003) and cross-collection mixture (ccMix) (Zhai et al., 2004) models on blogs and forums. We also provide a qualitative and quantitative analysis of the model on the cross-cultural data.

Original languageEnglish (US)
StatePublished - Aug 2009
EventImperical Methods in Natural Language Processing -
Duration: Aug 7 2009Aug 9 2009

Conference

ConferenceImperical Methods in Natural Language Processing
Period8/7/098/9/09

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Blogs
Chemical analysis

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Science Applications
  • Information Systems

Cite this

Paul, M., & Girju, R. (2009). Cross-cultural analysis of blogs and forums with mixed-collection topic models. Paper presented at Imperical Methods in Natural Language Processing, .

Cross-cultural analysis of blogs and forums with mixed-collection topic models. / Paul, Michael; Girju, Roxana.

2009. Paper presented at Imperical Methods in Natural Language Processing, .

Research output: Contribution to conferencePaper

Paul, M & Girju, R 2009, 'Cross-cultural analysis of blogs and forums with mixed-collection topic models', Paper presented at Imperical Methods in Natural Language Processing, 8/7/09 - 8/9/09.
Paul M, Girju R. Cross-cultural analysis of blogs and forums with mixed-collection topic models. 2009. Paper presented at Imperical Methods in Natural Language Processing, .
Paul, Michael ; Girju, Roxana. / Cross-cultural analysis of blogs and forums with mixed-collection topic models. Paper presented at Imperical Methods in Natural Language Processing, .
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