Initial CRAN submission.
tokenize_posts() — tokenizes a text column into a long-format token
table, with optional English stopword removal.cooccurrence_counts() — computes 2x2 contingency table counts (a, b, c,
d) for every pair of words meeting a minimum document-frequency threshold.word_orientation() — computes the phi coefficient for each word pair,
tests it for significance (chi-squared or Fisher's exact test for sparse
cells), applies a Benjamini-Hochberg correction across all tested pairs by
default, and classifies each pair as "attraction", "repulsion", or
"neutral".plot_orientation_network() — plots the strongest attraction and
repulsion word pairs as a network graph, using base igraph plotting.analyze_word_orientation() — a single-call pipeline wrapping the four
functions above, from raw text to a classified table and network plot.example_social_posts() — a small built-in toy dataset for examples and
tests.