Exploring long-term temporal trends in the use of Multiword Expressions

Differentiating between outdated expressions and current expressions is not a trivial task for foreign language learners, and could be beneficial for lexicographers, as they examine expressions. Assuming that the usage of expressions over time can be represented by a time-series of their periodic frequencies over a large lexicographic corpus, we test the hypothesis that there exists an old-new relationship between the time-series of some synonymous expressions, a hint that a later expression has replaced an earlier one. Another hypothesis we test is that Multiword Expressions (MWEs) can be characterized by sparsity & frequency thresholds. Using a dataset of 1 million English books, we choose MWEs having the most positive or the most negative usage trends from a ready-made list of known MWEs. We identify synonyms of those expressions in a historical thesaurus and visualize the temporal relationships between the resulting expression pairs. Our empirical results indicate that old-new usage relationships do exist between some synonymous expressions, and that new candidate expressions, not found in dictionaries, can be found by analyzing usage trends.