Award Date
May 2023
Degree Type
Thesis
Degree Name
Master of Arts (MA)
Department
Hank Greenspun School of Journalism and Media Studies
First Committee Member
Gregory Borchard
Second Committee Member
Kevin Stoker
Third Committee Member
David Nourse
Fourth Committee Member
Lawrence Mullen
Number of Pages
104
Abstract
With ever-advancing technology and the ubiquity of smart devices, younger generations of children are growing up with access to smart mobile technology from birth. These digitally acculturated children ages 0-5, or digitods, are learning to make sense of the world in large part through sociocultural exchanges in the home. As these digital natives are habituated to mobile media, prevalent and accessible, they are also opened to data-mining and target-marketing as their online engagement signals algorithmic function. This study adds to our understanding of how digitods may be susceptible to algorithmic culture and strategic digital marketing, as familial modeling and mediated exchanges position them to be active media users. Looking through the lens of Vygotsky’s Sociocultural Theory, that identifies children’s cognitive development as a product of social interactions and collaborative dialogues, this study takes an inductive and reflexive qualitative approach, utilizing a series of in-depth interviews of parents, to examine dynamics in the home.
Keywords
Algorithm Culture; Digitods; Familial Modeling; Internet Cognition; Mediated Exchanges; Sociocultural Learning
Disciplines
Communication | Sociology
File Format
Degree Grantor
University of Nevada, Las Vegas
Language
English
Repository Citation
Foley, Sina, "Digitods, Statistical Machine Learning Algorithms, and Internet Cognition: Sociocultural Learning through Familial Modeling and Mediated Exchanges" (2023). UNLV Theses, Dissertations, Professional Papers, and Capstones. 4680.
http://dx.doi.org/10.34917/36114705
Rights
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