| Title |
Nonnaïveté among Amazon Mechanical Turk workers: Consequences and solutions for behavioral researchers
|
|---|---|
| Published in |
Behavior Research Methods, July 2013
|
| DOI | 10.3758/s13428-013-0365-7 |
| Pubmed ID | |
| Authors |
Jesse Chandler, Pam Mueller, Gabriele Paolacci |
| Abstract |
Crowdsourcing services--particularly Amazon Mechanical Turk--have made it easy for behavioral scientists to recruit research participants. However, researchers have overlooked crucial differences between crowdsourcing and traditional recruitment methods that provide unique opportunities and challenges. We show that crowdsourced workers are likely to participate across multiple related experiments and that researchers are overzealous in the exclusion of research participants. We describe how both of these problems can be avoided using advanced interface features that also allow prescreening and longitudinal data collection. Using these techniques can minimize the effects of previously ignored drawbacks and expand the scope of crowdsourcing as a tool for psychological research. |
X Demographics
The data shown below were collected from the profiles of 13 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 23% |
| Canada | 2 | 15% |
| Netherlands | 2 | 15% |
| Norway | 1 | 8% |
| United Kingdom | 1 | 8% |
| Japan | 1 | 8% |
| Unknown | 3 | 23% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 7 | 54% |
| Members of the public | 6 | 46% |
Mendeley readers
The data shown below were compiled from readership statistics for 811 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 32 | 4% |
| United Kingdom | 10 | 1% |
| Germany | 4 | <1% |
| Spain | 3 | <1% |
| Chile | 2 | <1% |
| Japan | 2 | <1% |
| Canada | 2 | <1% |
| Hong Kong | 1 | <1% |
| Australia | 1 | <1% |
| Other | 7 | <1% |
| Unknown | 747 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 264 | 33% |
| Student > Master | 95 | 12% |
| Researcher | 69 | 9% |
| Student > Doctoral Student | 69 | 9% |
| Student > Bachelor | 53 | 7% |
| Other | 140 | 17% |
| Unknown | 121 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 288 | 36% |
| Social Sciences | 104 | 13% |
| Business, Management and Accounting | 95 | 12% |
| Computer Science | 45 | 6% |
| Economics, Econometrics and Finance | 29 | 4% |
| Other | 90 | 11% |
| Unknown | 160 | 20% |
Attention Score in Context
This research output has an Altmetric Attention Score of 27. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 05 October 2023.
All research outputs
#1,466,467
of 25,837,817 outputs
Outputs from Behavior Research Methods
#129
of 2,575 outputs
Outputs of similar age
#12,090
of 208,793 outputs
Outputs of similar age from Behavior Research Methods
#1
of 19 outputs
Altmetric has tracked 25,837,817 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,575 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.1. This one has done particularly well, scoring higher than 94% of its peers.
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We're also able to compare this research output to 19 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 94% of its contemporaries.