Automatic identification of words with novel but infrequent senses

We propose a statistical method for identifying words that have a novel sense in one corpus compared to another based on differences in their lexico-syntactic contexts in those corpora. In contrast to previous work on identifying semantic change, we focus specifically on infrequent word senses. Given the challenges of evaluation for this task, we further propose a novel evaluation method based on synthetic examples of semantic change that allows us to simulate differing degrees of sense change. Our proposed method is able to identify rather subtle simulated sense changes, and outperforms both a random baseline and a previously-proposed approach.