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Diachronic word embeddings -- vector representations of words over time --offer remarkable insights into the evolution of language and provide a tool forquantifying sociocultural change from text documents. Prior work has used suchembeddings to identify shifts in the meaning of individual words. However,simply knowing that a word has changed in meaning is insufficient to identifythe instances of word usage that convey the historical or the newer meaning. Inthis paper, we link diachronic word embeddings to documents, by situating thosedocuments as leaders or laggards with respect to ongoing semantic changes.Specifically, we propose a novel method to quantify the degree of semanticprogressiveness in each word usage, and then show how these usages can beaggregated to obtain scores for each document. We analyze two large collectionsof documents, representing legal opinions and scientific articles. Documentsthat are scored as semantically progressive receive a larger number ofcitations, indicating that they are especially influential. Our work thusprovides a new technique for identifying lexical semantic leaders anddemonstrates a new link between progressive use of language and influence in acitation network.

Follow the Leader: Documents on the Leading Edge of Semantic Change Get More Citations