  Different speakers often produce different names for the same object or
entity (e.g., "woman" vs. "tourist" for a female tourist). The reasons behind
variation in naming are not well understood. We create a Language and Vision
dataset for Mandarin Chinese that provides an average of 20 names for 1319
naturalistic images, and investigate how familiarity with a given kind of
object relates to the degree of naming variation it triggers across subjects.
We propose that familiarity influences naming variation in two competing ways:
increasing familiarity can either expand vocabulary, leading to higher
variation, or promote convergence on conventional names, thereby reducing
variation. We find evidence for both factors being at play. Our study
illustrates how computational resources can be used to address research
questions in Cognitive Science.
