{"pk":27073,"title":"Semantic Networks Generated from Early Linguistic Input","subtitle":null,"abstract":"Semantic networks generated from different word corporashow common structural characteristics, including high de-grees of clustering, short average path lengths, and scale freedegree distributions. Previous research has disagreed aboutwhether these features emerge from internally- or externally-driven properties (i.e. words already in the lexicon vs. regu-larities in the external world), mapping onto preferential at-tachment and preferential acquisition accounts, respectively(Steyvers & Tenenbaum, 2005; Hills, Maouene, Maouene,Sheya, & Smith, 2009). Such accounts suggest that inherentsemantic structure shapes new lexical growth. Here we ex-tend previous work by creating semantic networks using theSEEDLingS corpus, a newly collected corpus of linguistic in-put to infants. Using a recently developed LSA-like approach(GLoVe vectors), we confirm the presence of previously re-ported structural characteristics, but only in certain ranges ofsemantic similarity space. Our results confirm the robustnessof certain aspects of network organization, and provide novelevidence in support of preferential acquisition accounts.","language":"eng","license":{"name":"","short_name":"","text":null,"url":""},"keywords":[{"word":"semantic networks; word learning; preferential ac-quisition"}],"section":"Posters: Papers","is_remote":true,"remote_url":"https://escholarship.org/uc/item/99p6j5wb","frozenauthors":[{"first_name":"Andrei","middle_name":"","last_name":"Amatuni","name_suffix":"","institution":"Duke University","department":""},{"first_name":"Elika","middle_name":"","last_name":"Bergelson","name_suffix":"","institution":"Duke University","department":""}],"date_submitted":null,"date_accepted":null,"date_published":"2017-01-01T18:00:00Z","render_galley":null,"galleys":[{"label":"PDF","type":"pdf","path":"https://journalpub.escholarship.org/cognitivesciencesociety/article/27073/galley/16709/download/"}]}