A tale of two Americas : how rich and poor navigate the digital landscape

Placeholder Show Content

Abstract/Contents

Abstract
While social and economic inequalities in the digital landscape are a growing topic of research, there are large gaps in our knowledge of how low-income individuals engage with information online and how their digital experiences can translate into cognitive and emotional consequences. The present investigation fills these pressing gaps by combining economic principles with novel interdisciplinary research methods called Screenomics. Using Screenomics, we developed a unique dataset of more than 13 million screenshots (N = 13,498,584) taken every five seconds from the smartphones of low-income individuals and high-income individuals (N = 65) in U.S. metropolitan areas over a two-month period in 2019. This rich digital repository provides new insights into how economically disadvantaged individuals' information needs are (un)met in daily life, compared to more affluent peers. Topics include how individuals across income classes engaged with information in their roles as consumers, workers, audience members of entertainment, and voters (Study 1), how they encountered and reacted to targeted advertisements, such as payday loan ads (Study 2) and for-profit college ads (Study 3), and how individuals with low incomes faced obstacles to interacting with government websites and applications when they searched for social safety net assistance, including the Supplemental Nutrition Assistance Program (SNAP, formerly known as food stamps) and unemployment benefits (Study 4). The results show that various information demand and supply factors shaped individuals' online information lives. Consistent with the Downsian theory of rational ignorance about politics and policy, news consumption constituted only a small part of individuals' smartphone use in both income groups although low-income individuals spent significantly less time on news applications than their high-income counterparts. Digital content was generally supported by advertising for both income groups, while individuals with low incomes engaged in self-expression substantially more than individuals with high incomes. Another set of important findings highlights how encounters with content that can vex low-income individuals generate a scarcity mindset and what their smartphone use can reveal about their psychological stress. Negative digital experiences, such as exposures to payday loan ads and frustrating interactions with the government, taxed low-income individuals' cognitive and emotional resources, as evidenced by subsequent changes in consumption of future-oriented words and negative emotional words and in application switching. This dissertation enhances our understanding of how the current online information marketplace works for different income communities and the psychological consequences of disparate digital experiences, shifting the nature of the debates about digital infrastructure gaps into a new debate about content-level barriers and inequities.

Description

Type of resource text
Form electronic resource; remote; computer; online resource
Extent 1 online resource.
Place California
Place [Stanford, California]
Publisher [Stanford University]
Copyright date 2022; ©2022
Publication date 2022; 2022
Issuance monographic
Language English

Creators/Contributors

Author Lee, Jihye, (Researcher in communication)
Degree supervisor Hamilton, James, 1961-
Thesis advisor Hamilton, James, 1961-
Thesis advisor Hancock, Jeff
Thesis advisor Reeves, Byron, 1949-
Thesis advisor Robinson, Thomas (Thomas N.)
Degree committee member Hancock, Jeff
Degree committee member Reeves, Byron, 1949-
Degree committee member Robinson, Thomas (Thomas N.)
Associated with Stanford University, Department of Communication

Subjects

Genre Theses
Genre Text

Bibliographic information

Statement of responsibility Jihye Lee.
Note Submitted to the Department of Communication.
Thesis Thesis Ph.D. Stanford University 2022.
Location https://purl.stanford.edu/td603pv4386

Access conditions

Copyright
© 2022 by Jihye Lee
License
This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).

Also listed in

Loading usage metrics...