At TurkPrime, we advocate for requesters to treat workers fairly when posting HITs on Amazon’s Mechanical Turk (MTurk). Workers are, after all, the people who make the research possible. Sometimes situations arise in which an MTurk worker is unable to receive payment, despite having completed a survey. Below are two common scenarios in which a worker may not be paid, despite completing a survey:
Creating Compensation HITs for Mechanical Turk Workers
Topics: amazon mechanical turk, mechanical turk, compensating workers, how to compensate workers, how to compensate workers on TurkPrime
Running Dyadic Studies on Mechanical Turk using TurkPrime
Studying pairs of people (e.g., married couples, friends, coworkers, etc) is becoming increasingly commonplace in the social and behavioral sciences. Online participant populations, such as Mechanical Turk and other online panels, can potentially serve as a rich source of dyadic participants. However, conducting dyadic research online also faces multiple challenges that need to be overcome in order to obtain high quality results. This blog post will outline some of the challenges of running dyadic studies online, as well as the ways our MTurk Toolkit can best be used to run a dyadic study, with recommendations for best practices based on our experience. Using the methods outlined in this blog, researchers have been able to successfully run numerous dyadic studies using the MTurk Toolkit.
Topics: mechanical turk, romantic couples studies, dyadic studies, mturk toolkit
TurkPrime Tools to Help Combat Responses from Suspicious Geolocations
Last week, the research community was struck with concern that “bots” were contaminating data collection on Amazon’s Mechanical Turk (MTurk). We wrote about the issue and conducted our own preliminary investigation into the problem using the TurkPrime database. In this blog, we introduce two new tools TurkPrime is launching to help researchers combat suspicious activity on MTurk and reiterate some of the important takeaways from this conversation so far.
Topics: amazon mechanical turk, bots, mechanical turk, mturk, workers
Concerns about Bots on Mechanical Turk: Problems and Solutions
Data quality on online platforms
When researchers collect data online, it’s natural to be concerned about data quality. Participants aren’t in the lab, so researchers can’t see who is taking their survey, what those participants are doing while answering questions, or whether participants are who they say they are. Not knowing is unsettling.
Topics: bots, mechanical turk, mturk, quality, turkprime, workers
Some workers on MTurk are extremely active, and take the majority of posted HITs. This can lead to many issues, some of which are outlined in our previous post. Although MTurk has over 100,000 workers who take surveys each year, and around 25,000 who take surveys each month, you are much more likely to recruit highly active workers who take a majority of HITs. About 1,000 workers (1% of workers) take 21% of the HITs. About 10,000 workers (10% of workers) take 74% of all HITs.
Topics: active workers, amazon mechanical turk, exclude, exclude workers, HIT, mechanical turk, mturk, online research, turkprime, workers, active
Best recruitment practices: working with issues of non-naivete on MTurk
It is important to consider how many highly experienced workers there are on Mechanical Turk. As discussed in previous posts, there is a population pool of active workers in the thousands, but this is far from exhaustible. A small group of workers take a very large number of HITs posted to MTurk, and these workers are very experienced and have seen measures commonly used in the social and behavioral sciences. Research has shown that when participants are repeatedly exposed to the same measures, this can have negative effects on data collection, changing the way workers perform, creating treatment effects, giving participants insight into the purpose of some studies, and in some cases impact effect sizes of experimental manipulations. This issue is referred to as non-naivete (Chandler, 2014; Chandler, 2016).
Topics: amazon mechanical turk, approval rating, experience, exposure, HIT, mechanical turk, mturk, naivete, non-naive, primepanels, qualification, recruitment, requester, workers
Hundreds of academic papers are published each year using data collected through Mechanical Turk. Researchers have gravitated to Mechanical Turk primarily because it provides high quality data quickly and affordably. However, Mechanical Turk has strengths and weaknesses as a platform for data collection. While Mechanical Turk has revolutionized data collection, it is by no means a perfect platform. Some of the major strengths and limitations of MTurk are summarized below.
Topics: amazon mechanical turk, demographics, exclude workers, google form mechanical turk, HIT, mechanical turk, mturk, mturk api, panels, qualification, study, turkprime panels, unique worker, worker groups, workers
Studies with Panels for just $0.15 - 0.75 / complete
Now you can run Mechanical Turk studies using your own Requester account and specify over two dozen demographic traits!. The traits include gender, ethnicity, age, marital status and sexual orientation. But it does not stop there! The available options also include occupation, medical and health history, cell phone use and much more.
Topics: amazon mechanical turk, demographics, mechanical turk, mturk, qualification, traits, turkprime, turkprime panels
Google Forms can be used to deliver a study with TurkPrime in a similar manner to other survey platforms (like Qualtrics and SurveyMonkey).
Topics: google form mechanical turk, google forms, mechanical turk, mturk, secret code, secret key, survey, turkprime
Demographic Consistency Over Time on Mechanical Turk
Problem
Ever wonder if workers are being honest with you when they answer a survey? Or, if you specify that your study should be taken only by Women, whether some workers take the study even though they are not women?
Topics: amazon mechanical turk, demographics, gender gap, mechanical turk, mturk, panels