Crowdsourcing And Personality Measurement Equivalence: A Warning About Countries Whose Primary Language Is Not English
Keywords
Crowdsourcing; Data collection techniques; Invariance testing; Measurement; Survey methods
Abstract
In the search to find cheaper, faster approaches for data collection, crowdsourcing methods (i.e., online labor portals that allow independent workers to complete surveys for compensation) have risen in popularity as a tool for personality researchers, despite a lack of evidence regarding the equivalence of crowdsourcing with traditional data collection methods. The purpose of this study was to evaluate crowdsourcing as a data collection tool by examining the measurement equivalence of crowdsourced data (i.e., from Amazon.com's MTurk) with more traditional samples (i.e., an undergraduate sample and a sample of organizational employees). Our results (using a popular measure of Big Five personality) provided evidence of measurement equivalence across all three samples, with one important exception: crowdsourced data (from MTurk) only exhibited measurement invariance with traditional data collection methods when responses were restricted to participants from native-English speaking countries. Although MTurk appears to be an easy, cost-effective data collection tool, our results suggest that MTurk data are similar to traditionally-collected data only when the MTurk sample is restricted to IP addresses from English-speaking countries.
Publication Date
3-1-2015
Publication Title
Personality and Individual Differences
Volume
75
Number of Pages
47-52
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1016/j.paid.2014.11.017
Copyright Status
Unknown
Socpus ID
84911408250 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84911408250
STARS Citation
Feitosa, Jennifer; Joseph, Dana L.; and Newman, Daniel A., "Crowdsourcing And Personality Measurement Equivalence: A Warning About Countries Whose Primary Language Is Not English" (2015). Scopus Export 2015-2019. 904.
https://stars.library.ucf.edu/scopus2015/904