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Previous methods of analyzing the substance of political attention have had to make several restrictive assumptions or been prohibitively costly when applied to large-scale political texts. Here, we describe a topic model for legislative speech, a statistical learning model that uses word choices to infer topical categories covered in a set of speeches and(More)
We present a novel technique for speeding up the computation of PageRank, a hyperlink-based estimate of the " importance " of Web pages, based on the ideas presented in [7]. The original PageRank algorithm uses the Power Method to compute successive iterates that converge to the principal eigenvec-tor of the Markov matrix representing the Web link graph.(More)
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