(This post is co-written with Long Ouyang, a former graduate student in our department, who is the developer of nosub, and Manuel Bohn, a postdoc in my lab who has created a minimal working example).
Our typical workflow for AMT tasks is to create custom websites that guide participants through a series of linguistic stimuli of one sort or another. For simple questionnaires we often use Qualtrics, a commercial survey product, but most tasks that require more customization are easy to set up as free-standing javascript/HTML sites. These sites then need to be pushed to AMT as "external HITs" (Human Intelligence Tasks) so that workers can find them, participate, and be compensated.
nosub is a simple tool for accomplishing this process, building on earlier tools used by my lab.* The idea is simple: you customize your HIT settings in a configuration file and type
nosub upload
to upload your experiment to AMT. Then you can type
nosub download
to fetch results. Two nice features of nosub from a psychologist's perspective are: 1. worker IDs are anonymized by default so you don't need to worry about privacy issues (but they are deterministically hashed so you can still flag repeat workers), and 2. nosub can post HITs in batches so that you don't get charged Amazon's surcharge for tasks with more than 9 hits.
All you need to get started is to install Node.js; installation instructions for nosub are available in the project repository.
Once you've run nosub, you can download your data in JSON format, which can easily be parsed into R. We've put together a minimal working example of an experiment that can be run using nosub and a data analysis script in R that reads in the data.
Once you've run nosub, you can download your data in JSON format, which can easily be parsed into R. We've put together a minimal working example of an experiment that can be run using nosub and a data analysis script in R that reads in the data.
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* psiTurk is another framework that provides a way of serving and tracking HITs. psiTurk is great and we have used it for heavier-weight applications where we need to track participants, but can be tricky to debug and is not always compatible with some of our light-weight web experiments.