I'm currently using word_cor function (qdap package). I observed that the function is not robust as it implements Pearson, Spearman and Kendall measures only: non-occurrence of both words (in the following cross tabulation) also results in higher correlation, which should not be the case.
apply_as_df(v, word_cor, word = "hi", r=0.3, method="spearman")
Description of robustness: Correlation should not be affected by the value d - if both words don't occur in majority of documents, it doesn't mean they are highly correlated.
Is there a robust implementation of correlation/similarity (like Jaccard or cosine) for text mining in R?