The internet has the reputation of being a place where people can hide in anonymity, and present as being very different people than who they actually are. Is this a problem on Mechanical Turk? Is the self-reported information provided by Mechanical Turk workers reliable? These are important questions which have been addressed with several different methods. Researchers have examined a) consistency of responding to the same questions over time and across studies b) the validity of responses, or the degree to which the items capture responses that represent the truth from participants. It turns out that there are certain situations in which MTurk workers are likely to lie, but they are who they say they are in almost all cases.
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.
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Many researchers wish to target participants from specific states or regions of the United States like the Northeast or the West. The problem they often encounter is that using MTurk's Geographic Qualification to specify a particular state is often not adequate to ensure participants actually reside in the specified state.
What is the completion rate and dropout rate?
Dropout rate is defined as the percentage of participants who start taking a study but do not complete it. Dropout rate is sometimes referred to as attrition rate, and is the opposite of completion rate (dropout rate = 100 – completion rate). On MTurk, completion rate is defined as the number of Workers who submit a HIT divided by the number of Workers who accept the HIT. Note that, for the definition of completion rate used here, Rejected Workers are counted as completes.
Requesters may observe that some workers, even those with high Approval ratings, may not perform to their expectations on a study. Sometimes this may result in rejecting their work which affects the Worker approval rating. But, often the work is not acceptable for research but is not worthy of rejection, or, it may simply be the policy of the research lab to approve all assignments for IRB or some ethical standard they may follow.
You are running a longitudinal study and have identified 1000 workers who you want to allow to take your second phase studies. How do you easily group those workers for easy access.
Or you want to exclude certain workers from taking a number of your studies and wish to group them for easy exclusion in future studies. How can you do that?
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.
Have you ever wanted to run multiple studies simultaneously and make sure that each worker only takes a single study? On MTurk, there is no simple way to block workers who completed one study from accepting and completing another study being run at the same time....until now.
(Note: TurkPrime's exclude feature excludes workers who have completed one study from taking another subsequent study, but not if both studies are being run at the same time.)
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?