ERIC Number: EJ1390808
Record Type: Journal
Publication Date: 2023-Aug
Pages: 46
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-0049-1241
EISSN: EISSN-1552-8294
Curating Training Data for Reliable Large-Scale Visual Data Analysis: Lessons from Identifying Trash in Street View Imagery
Hwang, Jackelyn; Dahir, Nima; Sarukkai, Mayuka; Wright, Gabby
Sociological Methods & Research, v52 n3 p1155-1200 Aug 2023
Visual data have dramatically increased in quantity in the digital age, presenting new opportunities for social science research. However, the extensive time and labor costs to process and analyze these data with existing approaches limit their use. Computer vision methods hold promise but often require large and nonexistent training data to identify sociologically relevant variables. We present a cost-efficient method for curating training data that utilizes simple tasks and pairwise comparisons to interpret and analyze visual data at scale using computer vision. We apply our approach to the detection of trash levels across space and over time in millions of street-level images in three physically distinct US cities. By comparing to ratings produced in a controlled setting and utilizing computational methods, we demonstrate generally high reliability in the method and identify sources that limit it. Altogether, this approach expands how visual data can be used at a large scale in sociology.
Descriptors: Data Analysis, Visual Aids, Sanitation, Municipalities, Sociology, Social Science Research, Data Interpretation, Reliability, Artificial Intelligence
SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://bibliotheek.ehb.be:2993
Publication Type: Journal Articles; Reports - Evaluative
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Location: Massachusetts (Boston); Michigan (Detroit); California (Los Angeles)
Grant or Contract Numbers: N/A