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Autor/inn/enKoch, Alex; Speckmann, Felix; Unkelbach, Christian
TitelQ-SpAM: How to Efficiently Measure Similarity in Online Research
QuelleIn: Sociological Methods & Research, 51 (2022) 3, S.1442-1464 (23 Seiten)
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ZusatzinformationORCID (Koch, Alex)
Spracheenglisch
Dokumenttypgedruckt; online; Zeitschriftenaufsatz
ISSN0049-1241
DOI10.1177/0049124120914937
SchlagwörterMeasurement Techniques; Proximity; Social Science Research; Social Sciences; Stimuli; Computer Oriented Programs; Telecommunications; Computer Software; Research Methodology; Cognitive Processes; Behavior
AbstractMeasuring the similarity of stimuli is of great interest to a variety of social scientists. Spatial arrangement by dragging and dropping "more similar" targets closer together on the computer screen is a precise and efficient method to measure stimulus similarity. We present Qualtrics-spatial arrangement method (Q-SpAM), a feature-rich and user-friendly online version of spatial arrangement. Combined with crowdsourcing platforms, Q-SpAM provides fast and affordable access to similarity data even for large stimulus sets. Participants may spatially arrange up to 100 words or images, randomly selected targets, self-selected targets, self-generated targets, and targets self-marked in different colors. These and other Q-SpAM features can be combined. We exemplify how to collect, process, and visualize similarity data with Q-SpAM and provide R and Excel scripts to do so. We then illustrate Q-SpAM's versatility for social science, concluding that Q-SpAM is a reliable and valid method to measure the similarity of lots of stimuli with little effort. (As Provided).
AnmerkungenSAGE 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: http://sagepub.com
Erfasst vonERIC (Education Resources Information Center), Washington, DC
Update2024/1/01
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