wordorientation: Detect Attraction and Repulsion Between Words in Text
Provides tools to quantify how strongly pairs of words attract
or repel each other in a text corpus, based on co-occurrence patterns.
For each word pair, the phi coefficient (a correlation measure for binary
variables) is computed from a document-term matrix and tested for
significance, then classified as showing attraction (co-occurring more
than chance would predict), repulsion (co-occurring less than chance
would predict), or no significant relationship. A full pipeline is
provided from raw text to a labeled network visualization. Unlike
general-purpose pairwise correlation tools, 'wordorientation' is built
specifically for text: it handles tokenization and stopword removal,
applies significance-based classification rather than reporting a raw
correlation coefficient alone, and produces a ready-to-plot attraction/
repulsion network.
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=wordorientation
to link to this page.