diagnosys

Identify noisy documents in a corpus

internal

A word embeddings-based semi-supervised model for document scaling Watanabe (2020) <doi:10.1080/19312458.2020.1832976>.
LSS allows users to analyze large and complex corpora on arbitrary dimensions with seed words exploiting efficiency of word embeddings (SVD, Glove).
It can generate word vectors on a users-provided corpus or incorporate a pre-trained word vectors.

Kohei Watanabe

Semi-Supervised Algorithm for Document Scaling

diagnosys function

<dl><dt>x</dt>
<dd>character or <code>quanteda::corpus()</code> object whose texts will be diagnosed.</dd>
<dt>...</dt>
<dd>extra arguments passed to <code>quanteda::tokens()</code>.</dd></dl>

Arguments

Identify noisy documents in a corpus — diagnosys

<dl>

<dt>x</dt>
<dd>character or <code>quanteda::corpus()</code> object whose texts will be diagnosed.</dd>


<dt>...</dt>
<dd>extra arguments passed to <code>quanteda::tokens()</code>.</dd>

</dl>

diagnosys: Identify noisy documents in a corpus

Description

Usage

Arguments