| Literature DB >> 34666227 |
Abstract
Distributional models of lexical semantics have proven to be powerful accounts of how word meanings are acquired from the natural language environment (Günther, Rinaldi, & Marelli, 2019; Kumar, 2020). Standard models of this type acquire the meaning of words through the learning of word co-occurrence statistics across large corpora. However, these models ignore social and communicative aspects of language processing, which is considered central to usage-based and adaptive theories of language (Tomasello, 2003; Beckner et al., 2009). Johns (2021) recently demonstrated that integrating social and communicative information into a lexical strength measure allowed for benchmark fits to be attained for lexical organization data, indicating that the social world contains important statistical information for language learning and processing. Through the analysis of the communication patterns of over 330,000 individuals on the online forum Reddit, totaling approximately 55 billion words of text, the findings of the current article demonstrates that social information about word usage allows for unique aspects of a word's meaning to be acquired, providing a new pathway for distributional model development.Entities:
Keywords: Big data; Cognitive modeling; Distributional modeling; Lexical semantics; Machine learning
Mesh:
Year: 2021 PMID: 34666227 DOI: 10.1016/j.cogpsych.2021.101441
Source DB: PubMed Journal: Cogn Psychol ISSN: 0010-0285 Impact factor: 3.468