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sm_set_api_key(): Secure API key management via
environment variablessm_search_scopus(): Retrieve papers from Scopus with
automatic paginationsm_get_indexed_keywords(): Extract indexed keywords for
individual paperssm_preprocess_text(): Tokenize, remove stopwords, and
stem abstractssm_create_dtm(): Generate document-term matrices with
flexible filteringsm_select_optimal_k(): Coherence-based selection of
topic countsm_train_lda(): Train Latent Dirichlet Allocation
modelssm_compare_models(): Multi-model comparison (LDA, STM,
CTM) with metricssm_plot_topic_terms(): Bar charts of top terms per
topicsm_plot_topic_frequency(): Document distribution across
topicssm_plot_topic_trends(): Stacked percentage charts
showing temporal trendstheme_sportminer(): Custom colorblind-friendly ggplot2
themesm_keyword_network(): Co-occurrence network
visualizationtryCatch() for graceful error
handling.data pronoun
from rlangcat() or
print()R CMD check --as-cranskip_on_cran() for computationally
expensive operationsNote: This is the initial release. Future versions will include additional topic modeling algorithms, enhanced network analysis features, and extended visualization options.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.