Crowdsourcing research
Data collection with Amazon’s Mechanical Turk
Bibliographic Data
| ID | 12010992 |
|---|---|
| Authors | Kim Bartel Sheehan (University of Oregon, corresponding author) |
| Year | 2017 |
| Volume | 85 |
| Issue | 1 |
| Pages | 140-156 |
| Publication date | 2017-07-04 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Communication Monographs (JOURNAL) |
| Journal identifiers | ISSN: 0363-7751 • E-ISSN: 1479-5787 |
| Publisher | Taylor & Francis (PUBLISHER • GB) |
| DOI | 10.1080/03637751.2017.1342043 |
| OpenAlex | W2724582867 |
| Language | EN |
| Citations received | 111 |
| References cited | 42 |
Researchers in a variety of disciplines use Amazon’s crowdsourcing platform called Mechanical Turk as a way to collect data from a respondent pool that is much more diverse than a typical student sample. The platform also provides cost efficiencies over other online panel services and data can be collected very quickly. However, some researchers have been slower to try the platform, perhaps because of a lack of awareness of its functions or concerns with validity. This article provides an overview of Mechanical Turk as an academic research platform and a critical examination of its strengths and weaknesses for research. Guidelines for collecting data that address issues of validity, reliability, and ethics are presented
Amazon rainforest · Crowdsourcing · Data collection · Data science · Political science · Reliability (semiconductor · Respondent · Sample (material · Social science · Sociology · Strengths and weaknesses · Variety (cybernetics · World Wide Web · Computer Science · Digital Marketing and Social Media · Expert finding and Q&A systems · Mobile Crowdsensing and Crowdsourcing · Psychology · Social Psychology · Artificial Intelligence
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| Unique citing works | 111 |
|---|---|
| Citations per year | 12,33 |
| Citation span | 2017 - 2026 (10) |
| Citation velocity | current |
| Highly cited | Yes |
| Citation types | Neutral: 109 |