Date of Completion
11-14-2013
Embargo Period
11-14-2013
Advisors
Dr. Letitia Naigles; Dr. Whitney Tabor
Field of Study
Psychology
Degree
Master of Arts
Open Access
Open Access
Abstract
It is largely acknowledged that natural languages emerge from not just human brains, but also from rich communities of interacting human brains (de Boer, 2000; Galantucci et al., 2012; Senghas, 2005). Yet the precise role of such communities and such interaction on emergence of core properties of language has largely gone uninvestigated in naturally emerging systems, leaving the few existing computational investigations of this issue (de Boer, 2000, i.a.) somewhat ungrounded. Here we take a step towards investigating the precise role of community structure in the emergence of linguistic conventions with both naturalistic empirical data and computational modeling. We first show conventionalization of lexicons in two different classes of naturally emerging signed systems: (1) protolinguistic “homesigns” invented by linguistically isolated Deaf individuals, and (2) a natural sign language emerging in a recently formed rich Deaf community. We find that the latter conventionalized faster than the former. Second, we model conventionalization as a population of interacting individuals who adjust their probability of sign use in response to other individuals’ actual sign use. Simulations suggest that a richer social network, like that of natural (signed) languages, conventionalizes faster than a sparser social network, like that of homesign systems. We discuss our behavioral and computational results in light of other work on language emergence, other work of collective human behavior on complex networks, and other work on language development.
Recommended Citation
Richie, Russell, "Modeling the Emergence of Natural Language Lexicons" (2013). Master's Theses. 509.
https://digitalcommons.lib.uconn.edu/gs_theses/509
Major Advisor
Dr. Marie Coppola