Abstract
This study describes when and how adolescents engage with their fast-moving and dynamic digital environment as they go about their daily lives. We illustrate a new approach—screenomics—for capturing, visualizing, and analyzing screenomes, the record of individuals’ day-to-day digital experiences. Sample includes over 500,000 smartphone screenshots provided by four Latino/Hispanic youth, age 14 to 15 years, from low-income, racial/ethnic minority neighborhoods. Screenomes collected from smartphones for 1 to 3 months, as sequences of smartphone screenshots obtained every 5 seconds that the device is activated, are analyzed using computational machinery for processing images and text, machine learning algorithms, human labeling, and qualitative inquiry. Adolescents’ digital lives differ substantially across persons, days, hours, and minutes. Screenomes highlight the extent of switching among multiple applications, and how each adolescent is exposed to different content at different times for different durations—with apps, food-related content, and sentiment as illustrative examples. We propose that the screenome provides the fine granularity of data needed to study individuals’ digital lives, for testing existing theories about media use, and for generation of new theory about the interplay between digital media and development.
Original language | English (US) |
---|---|
Pages (from-to) | 16-50 |
Number of pages | 35 |
Journal | Journal of Adolescent Research |
Volume | 35 |
Issue number | 1 |
DOIs | |
State | Published - Jan 1 2020 |
All Science Journal Classification (ASJC) codes
- Developmental and Educational Psychology
- Sociology and Political Science
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In: Journal of Adolescent Research, Vol. 35, No. 1, 01.01.2020, p. 16-50.
Research output: Contribution to journal › Article › peer-review
TY - JOUR
T1 - Screenomics
T2 - A New Approach for Observing and Studying Individuals’ Digital Lives
AU - Ram, Nilam
AU - Yang, Xiao
AU - Cho, Mu Jung
AU - Brinberg, Miriam
AU - Muirhead, Fiona
AU - Reeves, Byron
AU - Robinson, Thomas N.
N1 - Funding Information: https://orcid.org/0000-0003-1671-5257 Ram Nilam 1 Yang Xiao 1 Cho Mu-Jung 2 Brinberg Miriam 1 Muirhead Fiona 3 Reeves Byron 2 Robinson Thomas N. 2 1 Pennsylvania State University, University Park, USA 2 Stanford University, CA, USA 3 University of Strathclyde, Glasgow, UK Nilam Ram, Department of Human Development & Family Studies, Pennsylvania State University, 407 Biobehavioral Health Building, University Park, PA 16802, USA. Email: [email protected] 10 2019 0743558419883362 © The Author(s) 2019 2019 SAGE Publications This study describes when and how adolescents engage with their fast-moving and dynamic digital environment as they go about their daily lives. We illustrate a new approach— screenomics —for capturing, visualizing, and analyzing screenomes, the record of individuals’ day-to-day digital experiences. Sample includes over 500,000 smartphone screenshots provided by four Latino/Hispanic youth, age 14 to 15 years, from low-income, racial/ethnic minority neighborhoods. Screenomes collected from smartphones for 1 to 3 months, as sequences of smartphone screenshots obtained every 5 seconds that the device is activated, are analyzed using computational machinery for processing images and text, machine learning algorithms, human labeling, and qualitative inquiry. Adolescents’ digital lives differ substantially across persons, days, hours, and minutes. Screenomes highlight the extent of switching among multiple applications, and how each adolescent is exposed to different content at different times for different durations—with apps, food-related content, and sentiment as illustrative examples. We propose that the screenome provides the fine granularity of data needed to study individuals’ digital lives, for testing existing theories about media use, and for generation of new theory about the interplay between digital media and development. screenomics screenome smartphone social media adolescence digital media intensive longitudinal data experience sampling National Institute on Aging https://doi.org/10.13039/100000049 T32 AG049676 national institutes of health https://doi.org/10.13039/100000002 UL1 TR002014 stanford university https://doi.org/10.13039/100005492 Stanford Child Health Research Institute Stanford University PHIND Center john s. and james l. knight foundation https://doi.org/10.13039/100005959 G-2017-54227 national science foundation https://doi.org/10.13039/100000001 social science research institute, pennsylvania state university https://doi.org/10.13039/100007164 edited-state corrected-proof Thanks very much to the study participants for providing a detailed glimpse of their daily lives for such an extended period of time. Declaration of Conflicting Interests The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Funding The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Authors’ contributions supported by the Cyber Social Initiative at Stanford University (SPO#125124), the Stanford Child Health Research Institute, The Stanford University PHIND Center (Precision Health and Integrated Diagnostics), the Knight Foundation (G-2017-54227), the National Institute on Health (UL1 TR002014, T32 AG049676, T32 LM012415), National Science Foundation (I/UCRC award #1624727), and the Penn State Social Science Research Institute. ORCID iD Nilam Ram https://orcid.org/0000-0003-1671-5257 Funding Information: Thanks very much to the study participants for providing a detailed glimpse of their daily lives for such an extended period of time. The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Authors? contributions supported by the Cyber Social Initiative at Stanford University (SPO#125124), the Stanford Child Health Research Institute, The Stanford University PHIND Center (Precision Health and Integrated Diagnostics), the Knight Foundation (G-2017-54227), the National Institute on Health (UL1 TR002014, T32 AG049676, T32 LM012415), National Science Foundation (I/UCRC award #1624727), and the Penn State Social Science Research Institute. Publisher Copyright: © The Author(s) 2019.
PY - 2020/1/1
Y1 - 2020/1/1
N2 - This study describes when and how adolescents engage with their fast-moving and dynamic digital environment as they go about their daily lives. We illustrate a new approach—screenomics—for capturing, visualizing, and analyzing screenomes, the record of individuals’ day-to-day digital experiences. Sample includes over 500,000 smartphone screenshots provided by four Latino/Hispanic youth, age 14 to 15 years, from low-income, racial/ethnic minority neighborhoods. Screenomes collected from smartphones for 1 to 3 months, as sequences of smartphone screenshots obtained every 5 seconds that the device is activated, are analyzed using computational machinery for processing images and text, machine learning algorithms, human labeling, and qualitative inquiry. Adolescents’ digital lives differ substantially across persons, days, hours, and minutes. Screenomes highlight the extent of switching among multiple applications, and how each adolescent is exposed to different content at different times for different durations—with apps, food-related content, and sentiment as illustrative examples. We propose that the screenome provides the fine granularity of data needed to study individuals’ digital lives, for testing existing theories about media use, and for generation of new theory about the interplay between digital media and development.
AB - This study describes when and how adolescents engage with their fast-moving and dynamic digital environment as they go about their daily lives. We illustrate a new approach—screenomics—for capturing, visualizing, and analyzing screenomes, the record of individuals’ day-to-day digital experiences. Sample includes over 500,000 smartphone screenshots provided by four Latino/Hispanic youth, age 14 to 15 years, from low-income, racial/ethnic minority neighborhoods. Screenomes collected from smartphones for 1 to 3 months, as sequences of smartphone screenshots obtained every 5 seconds that the device is activated, are analyzed using computational machinery for processing images and text, machine learning algorithms, human labeling, and qualitative inquiry. Adolescents’ digital lives differ substantially across persons, days, hours, and minutes. Screenomes highlight the extent of switching among multiple applications, and how each adolescent is exposed to different content at different times for different durations—with apps, food-related content, and sentiment as illustrative examples. We propose that the screenome provides the fine granularity of data needed to study individuals’ digital lives, for testing existing theories about media use, and for generation of new theory about the interplay between digital media and development.
UR - http://www.scopus.com/inward/record.url?scp=85074858872&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85074858872&partnerID=8YFLogxK
U2 - 10.1177/0743558419883362
DO - 10.1177/0743558419883362
M3 - Article
C2 - 32161431
AN - SCOPUS:85074858872
SN - 0743-5584
VL - 35
SP - 16
EP - 50
JO - Journal of Adolescent Research
JF - Journal of Adolescent Research
IS - 1
ER -