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SportMiner needs stm, which CRAN will archive unless its check problems are fixed by Nov 13.

SportMiner

0.1.0Package record

Text Mining and Topic Modeling for Sport Science Literature

0packages depend
1.8Kdownloads / year
57.0%test coverage
13/13flavors OK

Overview

About

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'.

Changes in 0.1.0

Initial CRAN Release

New Features

  • **API Functions**
  • sm_set_api_key(): Secure API key management via environment variables
  • sm_search_scopus(): Retrieve papers from Scopus with automatic pagination
  • sm_get_indexed_keywords(): Extract indexed keywords for individual papers
  • **Text Processing**
  • sm_preprocess_text(): Tokenize, remove stopwords, and stem abstracts
  • sm_create_dtm(): Generate document-term matrices with flexible filtering
  • **Topic Modeling**
  • sm_select_optimal_k(): Coherence-based selection of topic count
  • sm_train_lda(): Train Latent Dirichlet Allocation models
Show all changes in 0.1.0Hide the rest of the changes in 0.1.0
  • sm_compare_models(): Multi-model comparison (LDA, STM, CTM) with metrics
  • **Visualizations**
  • sm_plot_topic_terms(): Bar charts of top terms per topic
  • sm_plot_topic_frequency(): Document distribution across topics
  • sm_plot_topic_trends(): Stacked percentage charts showing temporal trends
  • theme_sportminer(): Custom colorblind-friendly ggplot2 theme
  • **Network Analysis**
  • sm_keyword_network(): Co-occurrence network visualization

CRAN Compliance

  • All API calls wrapped in tryCatch() for graceful error handling
  • Global variables properly declared using .data pronoun from rlang
  • Message/warning functions used instead of cat() or print()
  • Comprehensive test suite with offline-safe mocks via httptest
  • Zero errors, warnings, or notes in R CMD check --as-cran

Documentation

  • Complete roxygen2 documentation for all exported functions
  • "Getting Started" vignette with end-to-end workflow example
  • README with quick start guide and advanced usage examples

Testing

  • 30+ unit tests covering all major functions
  • Edge case handling (empty data, missing columns, invalid parameters)
  • Mock API responses for offline testing
  • Tests marked with skip_on_cran() for computationally expensive operations

---

**Note**: This is the initial release. Future versions will include additional topic modeling algorithms, enhanced network analysis features, and extended visualization options.

From NEWS.md in the release

Install

Health

CRAN checks
13OK
Slowest check: 3.1 min · r-oldrel-windows-x86_64
Status changes
  • OK13 OK2026-10-12
  • ERROR12 OK, 1 ERROR2026-10-09
  • OK13 OK2026-09-08
  • ERROR12 OK, 1 ERROR2026-09-07
  • OK13 OK2026-08-05
Show 6 earlier changesHide 6 earlier changes
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK13 OK2026-06-09
  • ERROR12 OK, 1 ERROR2026-06-08
  • OK14 OK2026-04-10
  • ERROR13 OK, 1 ERROR2026-04-09
  • OK14 OK2026-03-10
Advisories

none known

Documentation

In release 0.1.0
READMEYes · 366 wordsVignettesYes · 2 · staticNEWSYes · 67% structured · mentions 0.1.0Citation fileYes · software entry onlyWebsitenot declared in DESCRIPTION
Help pages
18 (5 internal)includes a package overview page
Examples that run
8%1 run in a plain check · 12 never run
Exported functions with examples
100%
Documented parameters
99%
Return-value docs
100%
Help pages citing references
0%

Downloads

1.8K
CRAN downloads in the past year
Rank #23,242 · ~5/day · ~147/mo
Daily download trend is not available in this view yet.
19330 days
56490 days
1.8K1 year
Compare downloads with other packages →
Also on49 r2u

Repository

0Stars
0Forks
0Open issues
0Open PRs
0Releases
biomechanicspackagephdr-packagesports-science
Last activity 2026-08-20
Responsiveness
not measured
PracticesBeta

5 development-tooling and community-health practices detected across 4 families in the upstream repository

Checks run against github.com/praveenmaths89/sportminer on 2026-10-21.

Governance and community (1)
Contributing guide
Reproducibility and dev environment (1)
data-raw/
CRAN release process (1)
cran-comments.md
Research and citation (2)
CITATION.cffJOSS paper
How this is detected·Detection ruleset v4 (2026-10-20)
AI coding toolsBeta

This repository shows signs of AI coding tools.

  • Cursorfirst seen 2026-08-20
    Commits: at least 2 crediting it in the message
Counts are commits, not lines of code. Commits by a tool's accounts count once across all of its accounts. Commits crediting it are the largest count among its credit lines, a minimum.How this is detected·Detection ruleset v4 (updated 2026-09-27)

Dependencies

Declared dependencies
20 external dependencies (excludes base and recommended)

Installing SportMiner adds 97 packages (63 with compiled code, 99 MB of source tarballs). Heaviest: BH 14 MB, stringi 11 MB, ggplot2 6.0 MB.

Depends (1)
R >= 4.0.0
LinkingTo (0)
none
Enhances (0)
none
Dependencies facing archival

CRAN will archive these unless their check problems are fixed by the date shown. This package needs each one to install.

  • stmfix by Nov 13
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

People & History

People (2)
Author, Maintainer since 0.1.0 (2026)
Releases (1)
  • R
    R 4.6.0 released · 2026-04-24
  • 0.1.0Latest
    2026-01-17 · current release
  • R
    R 4.5.0 released · 2025-04-11

Package metadata

First published
2026-01-17
Total releases
1 / 1 yrs
License
MIT + file LICENSE OSI
Minimum R
≥ 4.0.0
Download size
61 KB

Cite

Cite this package

Run in R for the authors' entry:

citation("SportMiner")

The package provides a citation file, so citation() returns the authors' own entry.

The repository also keeps a CITATION.cff.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for SportMiner version 0.1.0 [Data set]. HJJB, LLC. Data release v2026-10-24. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-24, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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