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This project is a part of the Data Science Working Group at Code for San Francisco. It was initiated in order to provide all Code for America brigades with a tool for performing user research with Twitter data. Other DSWG projects can be found at the main GitHub repo.
For machine learning (ML) to be effective, models need accurately labeled data examples against which predictions can be compared. Getting labeled data is a time consuming exercise requiring multiple people spending hours of time. Twabler intends to provide projects with an application that simplifies the process of uploading datasets, configuring the labeling job, onboarding labelers, and managing the progress, while at the same time providing labelers with an easy to use mobile client application for efficiently labeling as many data examples as possible whenever they have their smart phone and some free time.
Yes, there are commercial applications that provide these resources, but we want to provide an open source solution to any organization with no more resources than a computer and volunteers with cell phones.
Currently, we are working on both iOS and Android client apps and a web app for the admin interface. We are still in the process of scoping features and designing the architecture.
- If you haven't joined the SF Brigade Slack, you can do that here.
- Our slack channel is
#twabler - Feel free to contact @Josh Freivogel, @Bob (Bob Lee), or @Ariel Takvam on slack with any questions or if you are interested in contributing!