When you link an Amazon Mechanical Turk account to TurkPrime, you can run studies on Mechanical Turk while using TurkPrime features meant to simplify setting up and managing studies. In order for TurkPrime to communicate with MTurk, you must create an Amazon Web Services account and give TurkPrime permission to interact with your Amazon account. If you have been through this process, you may remember creating an “Identity Access Management” (IAM) user and entering the secret key and secret access keys generated for this user into TurkPrime. In this blog, we touch on an aspect of account security related to these access keys. Specifically, we describe how you can easily rotate your secret access keys—similar to changing a password—and why you would want to.
In a recent research article (https://psyarxiv.com/jq589/), we reported that there are 250,810 MTurk workers worldwide who have completed at least one Human Intelligence Task (HIT) posted through the TurkPrime platform. More than 226,500 of these workers are based in the US.
By now, most people have heard of the gig economy and have some idea of how it works. In the gig economy, people perform short-term jobs or tasks to earn money. Gig economy jobs are considered independent or contract work, meaning people who work in the gig economy often trade the benefits and stability of traditional employment for the freedom and flexibility to decide when and how much they work. Some of the most easily identifiable gig economy platforms are Uber, Lyft, AirBnB, and the slightly less mentioned Mechanical Turk or MTurk.
A persistent cause of concern for researchers who conduct studies online is understanding what participants might be doing while completing their study. When participants are outside the lab, they cannot be observed and distracting aspects of the environment cannot be controlled by the research team. As a result, researchers are left to wonder: how much attention are participants giving my survey?
In this blog, we report on one small aspect of this issue by describing the work style adopted by workers on Amazon’s Mechanical Turk.
Last month, we published a blog titled, “Five Things you Should Not be Doing in Online Data Collection.” Among the things we identified that you should not be doing was launching your study without piloting it first. As a way to reiterate how important we think this issue is, we describe in this blog how to easily conduct a pilot study using TurkPrime.
Academic research is a collaborative endeavor. Faculty members work with post-docs, grad students, and undergrads. Sometimes one lab collaborates with another. During the course of such work, resources sometimes need to be shared or redistributed. At TurkPrime, we have sought to make part of this sharing easier by allowing researchers to transfer funds from one user’s lab balance to another. In this blog, we demonstrate how to use this feature.
One reason Amazon Mechanical Turk has become so popular among researchers is the speed with which data can be collected. Compared to more traditional research methods—lab-based experiments, field studies, ethnographic interviews, etc—MTurk is exceptionally fast, making it possible to collect data for an entire study within a day or sometimes just a few hours. Although MTurk’s speed is nice, there are times when collecting data all at once can actually be a problem. In this blog, we explain how to spread your data collection out across time and why you might want to do so.
In this blog, we highlight some subtle and not so subtle aspects of the TurkPrime Dashboard you can use to make navigation and completing study-related tasks easier.
Three weeks ago, we published a blog explaining five things you should be doing in your online data collection. In this blog, we follow up with five things you should NOT be doing when collecting data on MTurk.