The impostor among us: how to detect bots in online questionnaires
Carmen Cervone (University of Padova)
With online studies, researchers are constantly at risk of bad data quality. In the past few years, concern has increased about “bots” completing online surveys, starting from 2018 when some researchers noticed suspicious data in their MTurk samples, most tagged to the same geolocation (“survey farms”). According to some, the “bots” reached 20-30% of their samples, though it is argued that most were actually low-quality human data with fake VPNs (i.e., fraudulent data). This issue is prevalent to MTurk, and other platforms (e.g., Prolific Academic) appear to be safe, but detection tools may still be useful to improve data quality. In this presentation I will describe the issue, and present pros and cons of various detection methods.
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