Stability in the temporal dynamics of word meanings

Words show complex dynamics of meaning change. In some cases, a word may acquire novel senses. In other cases, existing senses of a word may become obsolete. The rates at which words gain and lose senses may vary, but it is an open question which factors might account for this variation. Building on work in computational linguistics and cognitive science, we develop a computational approach that explores this question by leveraging word sense records from a large historical database of English. Our results suggest that polysemous words tend to gain and lose senses more than words with fewer senses, and that these effects are robust when word frequency and length are both controlled for. These results are consistent with recent findings on the mechanisms of emergent word meanings and they further suggest stability in the temporal dynamics of word meanings.

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