Modelling and Predicting Online Vaccination Views using Bow-tie Decomposition: Dataset & Code

Here we document the dataset and the programming code used in our paper "Modelling and Predicting Online Vaccination Views using Bow-tie Decomposition", Royal Society Open Science (2024). In this paper, we investigate a temporal dataset that describes the Facebook vaccination views campaign in network representations, involving nearly 100 million users on Facebook from across countries, continents and languages.

It was provided by Johnson et al. (2020) and Illari et al. (2022) spanning different time periods. The former contains two snapshots in February 2019 and October 2019 (before the COVID-19), which we study in our main paper. The latter contains another two snapshots in November 2019 and December 2020 (at the initial stage of the COVID-19), which we study in Supplementary Material. Both of them are openly available and documented in two papers separately of different formats (PDF & Excel), thus requiring intensive preprocessing.

To make it easier for other researchers to use this dataset, here we reorganise both versions of this dataset in gpickle format (can be directly imported as attributed networks using Python) and in CSV format (for general use of the dataset).