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Q-SpAM: How to Efficiently Measure Similarity in Online Research

Author

Listed:
  • Alex Koch
  • Felix Speckmann
  • Christian Unkelbach

Abstract

Measuring 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.

Suggested Citation

  • Alex Koch & Felix Speckmann & Christian Unkelbach, 2022. "Q-SpAM: How to Efficiently Measure Similarity in Online Research," Sociological Methods & Research, , vol. 51(3), pages 1442-1464, August.
    • Handle: RePEc:sae:somere:v:51:y:2022:i:3:p:1442-1464
    DOI: 10.1177/0049124120914937
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    References listed on IDEAS

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    1. Michael C Hout & Stephen D Goldinger & Kyle J Brady, 2014. "MM-MDS: A Multidimensional Scaling Database with Similarity Ratings for 240 Object Categories from the Massive Memory Picture Database," PLOS ONE, Public Library of Science, vol. 9(11), pages 1-11, November.
    2. Joseph Henrich & Steve J. Heine & Ara Norenzayan, 2010. "The Weirdest People in the World?," RatSWD Working Papers 139, German Data Forum (RatSWD).
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