Supervised learning models to predict engagement for Facebook and Twitter posts. Developed using the Scikit-learn Python machine learning library.
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Supervised learning models to predict engagement rate of Facebook and Twitter posts developed using the Scikit-learn python machine learning library.

Repository content

The /scripts folder contains the script to extract the social media posts using the Facebook Graph API and Twitter REST API respectively.

The /classifiers folder contains the three classifiers developed for this project: Decision Tree, Naive Bayes, and linear model with SGD training.


The findings of this project are published in the Computers in Human Behavior Journal.


Hwong, Y. L., Oliver, C., Van Kranendonk, M., Sammut, C., & Seroussi, Y. (2017). What makes you tick? The psychology of social media engagement in space science communication. Computers in Human Behavior, 68, 480-492.

Paper can be downloaded here