TITLE

APPLYING PROBABILISTIC TOPIC MODELS TO BLOG COMMUNITIES

AUTHOR(S)
Berlea, Alexandru
PUB. DATE
January 2009
SOURCE
Proceedings of the IADIS International Conference on WWW/Interne;Jan2009, p324
SOURCE TYPE
Conference Proceeding
DOC. TYPE
Article
ABSTRACT
The popularity of Internet communities makes the content generated by their users increasingly interesting for various purposes, including business ones. Analyzing the typically huge amount of community generated content calls for automatic methods, a fundamental task hereby being to automatically detect the discussion topics. One very promising approach thereto are probabilistic topic models (PTMs). In this paper we report our experiences with applying PTMs to one popular Internet community. We discuss and interpret practical decisions to take for the application of PTMs and the results obtained on our data. The particularities of PTMs in the context of typical blog collections are addressed. In particular, we suggest how topic detection can benefit from typical blog features and also how the topic information can be exploited for better supporting communities and for gaining relevant information from them.
ACCESSION #
63694251

 

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