SportMiner 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
  • 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.