Predicting the Rate of Novel Words from Word-Level Semantic Measures in a Taboo Game Setting

The present study investigates novel word production rates for existing concepts, expressed by single words. To capture a wide variety of semantic nuances that influence individual processes of word creation, we quantify the distributional, categorical and psychological properties of single words. These features are tested for their correlation with novel word response rates in an online study employing the Taboo Game Paradigm. Speakers are presented with a word whose meaning they must express as accurately as possible with a single word without using the target word itself. Based on our experimental results, we conclude that words with higher distributional vector norms have a higher likelihood of being expressed through a novel word. We also find that participants produce a higher rate of novel words for more concrete items, as well as for items that have lower connectivity within a network of taxonomically related words. These results are interpreted in the light of theories about the production of words.