read_dfm_cpp

Read files from the quanteda dfm (this is the same as dgCMatrix)

internal

Fits keyword assisted topic models (keyATM) using collapsed Gibbs samplers. The keyATM combines the latent dirichlet allocation (LDA) models with a small number of keywords selected by researchers in order to improve the interpretability and topic classification of the LDA. The keyATM can also incorporate covariates and directly model time trends. The keyATM is proposed in Eshima, Imai, and Sasaki (2024) <doi:10.1111/ajps.12779>.

Shusei Eshima

keyATM

Keyword Assisted Topic Models

Tomoya Sasaki

Kosuke Imai

Chung-hong Chan

Romain François

Martin Feldkircher

William Lowe

Seo-young Silvia Kim

read_dfm_cpp function

<dl><dt>dfm</dt>
<dd>a dfm input (sparse Matrix)</dd>
<dt>W_read</dt>
<dd>an object to return</dd>
<dt>vocab</dt>
<dd>a vector of vocabulary</dd>
<dt>split</dt>
<dd>split proportion</dd></dl>

Arguments

Read files from the quanteda dfm (this is the same as dgCMatrix) — read_dfm_cpp

<dl>

<dt>dfm</dt>
<dd>a dfm input (sparse Matrix)</dd>


<dt>W_read</dt>
<dd>an object to return</dd>


<dt>vocab</dt>
<dd>a vector of vocabulary</dd>


<dt>split</dt>
<dd>split proportion</dd>

</dl>

Read files from the quanteda dfm (this is the same as dgCMatrix)

read_dfm_cpp: Read files from the quanteda dfm (this is the same as dgCMatrix)

Description

Usage

Arguments