Please use this identifier to cite or link to this item:
http://arks.princeton.edu/ark:/88435/dsp01ms35tc80s
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Stewart, Brandon | - |
dc.contributor.author | Shawa, Tara | - |
dc.date.accessioned | 2022-07-18T14:25:48Z | - |
dc.date.available | 2022-07-18T14:25:48Z | - |
dc.date.created | 2022-04-18 | - |
dc.date.issued | 2022-07-18 | - |
dc.identifier.uri | http://arks.princeton.edu/ark:/88435/dsp01ms35tc80s | - |
dc.description.abstract | The focus of this thesis lies in the intersection between childhood gender socialization, media effects, and digital technology. The research question is twofold: first, how is gender represented in content on the YouTube Kids platform? And second, to what extent does the recommendation system reinforce these gendered representations? To address these questions, I begin with a review of literature in the key fields that intersect on this topic. I start with gender theory and childhood socialization theory, then media effects and digital media, and lastly the platform through which they convene: YouTube Kids. Grounded in this cumulative knowledge, I conduct a mixed-method analysis, comprised of qualitative case studies and quantitative content analysis, to examine representations of gender and their potential exacerbation throughout various types of content. I find that gendered representations on YouTube Kids reflect normative constructions of gender, and that there is potential for the platform’s recommendation system to suggest increasingly gendered content to users. | en_US |
dc.format.mimetype | application/pdf | - |
dc.language.iso | en | en_US |
dc.title | Technological Gender Socialization: Examining Gender Representation and Reinforcement through the YouTube Kids Recommendation System | en_US |
dc.type | Princeton University Senior Theses | - |
pu.date.classyear | 2022 | en_US |
pu.department | Sociology | en_US |
pu.pdf.coverpage | SeniorThesisCoverPage | - |
pu.contributor.authorid | 920209817 | - |
pu.certificate | Center for Statistics and Machine Learning | en_US |
pu.certificate | Program in Gender and Sexuality Studies | - |
pu.certificate | Program in Technology & Society, Technology Track | - |
pu.mudd.walkin | No | en_US |
Appears in Collections: | Sociology, 1954-2023 |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
SHAWA-TARA-THESIS.pdf | 1.7 MB | Adobe PDF | Request a copy |
Items in Dataspace are protected by copyright, with all rights reserved, unless otherwise indicated.