wordorientation 0.1.0

Initial CRAN submission.

Features

• 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,
  4. 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.