theme_sportminer

A clean, professional, and colorblind-friendly ggplot2 theme designed
for academic publications and presentations in sport science.

A comprehensive toolkit for mining, analyzing, and visualizing
scientific literature in sport science domains. Provides functions for
retrieving abstracts from 'Scopus', preprocessing text data, performing
advanced topic modeling using Latent Dirichlet Allocation ('LDA'),
Structural Topic Models ('STM'), and Correlated Topic Models ('CTM'),
and creating publication-ready visualizations including keyword
co-occurrence networks and topic trends. For methodological details see
Blei et al. (2003) <doi:10.1162/jmlr.2003.3.4-5.993> for 'LDA',
Roberts et al. (2014) <doi:10.1111/ajps.12103> for 'STM', and
Blei and Lafferty (2007) <doi:10.1214/07-AOAS114> for 'CTM'.

Praveen D Chougale

SportMiner

Text Mining and Topic Modeling for Sport Science Literature

theme_sportminer function

<dl><dt>base_size</dt>
<dd>Base font size in points. Default is 11.</dd>
<dt>base_family</dt>
<dd>Base font family. Default is "".</dd>
<dt>grid</dt>
<dd>Logical indicating whether to display grid lines.
Default is TRUE.</dd></dl>

Arguments

SportMiner Custom ggplot2 Theme — theme_sportminer

<dl>

<dt>base_size</dt>
<dd>Base font size in points. Default is 11.</dd>


<dt>base_family</dt>
<dd>Base font family. Default is "".</dd>


<dt>grid</dt>
<dd>Logical indicating whether to display grid lines.
Default is TRUE.</dd>

</dl>

theme_sportminer: SportMiner Custom ggplot2 Theme

Description

Usage

Value

Arguments

Examples