Rapid Semantic Integration of Novel Words Following Exposure to Distributional Regularities

AbstractOur knowledge of words consists of a lexico-semantic network in which different words and their meanings are connected by relations, such as similarity in meaning. This research investigated the integration of new words into lexico-semantic networks. Specifically, we investigated whether new words can rapidly become linked with familiar words given exposure to distributional regularities that are ubiquitous in real-world language input, in which familiar and new words either directly co-occur in sentences, or share patterns of co-occurrence with another word. We observed that, immediately after sentence reading, familiar words came to be primed by both new words with which they co-occurred in sentences, and new words with which they shared co-occurrence. This finding represents a novel demonstration that new words can be rapidly integrated into lexico-semantic networks from exposure to distributional regularities.

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