Year: 2014
Type: dissertation
Abstract: We develop a Network Based Topic Model (NBTM), which integrates a Random Graph model with the Latent Dirichlet Allocation (LDA) model. The NBTM assumes that the topic proportion of a document has a xed variance across the document corpus with author dierences treated as random eects. It also assumes that the links between documents are binary variables whose probabilities depend upon the author random eects. We t the model to political blog posts during the calendar year 2012 that mention Trayvon Martin. This paper presents the topic extraction results and posterior prediction results for hidden links within the blogosphere.
Source: DukeSpace (Duke University)
Author: Liang Jiawei
Language: English
Subfield: General Social Sciences
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W2138419150