Running experiments on Amazon Mechanical Turk
Why is this work in the frame?
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
No Canadian affiliation. An affiliation-only frame — the usual design — would never have seen this work. It is one of the works that make the case for inverting the frame.
Abstract
Abstract Although Mechanical Turk has recently become popular among social scientists as a source of experimental data, doubts may linger about the quality of data provided by subjects recruited from online labor markets. We address these potential concerns by presenting new demographic data about the Mechanical Turk subject population, reviewing the strengths of Mechanical Turk relative to other online and offline methods of recruiting subjects, and comparing the magnitude of effects obtained using Mechanical Turk and traditional subject pools. We further discuss some additional benefits such as the possibility of longitudinal, cross cultural and prescreening designs, and offer some advice on how to best manage a common subject pool.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
The record
- Venue
- Judgment and Decision Making
- Topic
- Mobile Crowdsensing and Crowdsourcing
- Field
- Computer Science
- Canadian institutions
- —
- Funders
- York UniversityNational Science Foundation
- Keywords
- Amazon rainforestSubject (documents)Data scienceQuality (philosophy)Social mediaPopulationComputer scienceData qualityInternet privacyWorld Wide WebEngineeringSociologyOperations managementPhysicsDemography
- Has abstract in OpenAlex
- yes