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Tutorials for getting the most out of Twitter data.

Do more with Twitter data

We’re a group of data scientists on the Twitter Data team who are helping people do more with Twitter data in less time. Each of the posts in this example series provides a tutorial and reproducible case study of getting value from Twitter data.

Each post's source code and installation is in a subfolder in ./examples/. We make heavy use of the PyData stack on our team and each post is written and developed in Python, though the steps to reproduce the analyses can be done in any language with good machine-learning and data manipulation libraries. Each post is primarily a Jupyter notebook and provides a pip-installable requirements file and a conda environment for easy setup.

Please reach out to Aaron either via Twitter with any comments, questions, or thoughts.