Data for Ideological biases in social sharing of online information about climate change

This repository contains an anonymised dataset to support the paper "Ideological biases in social sharing of online information about climate change" by Tristan J.B. Cann, Iain S. Weaver and Hywel T.P. Williams, submitted for publication in PLOS ONE.

The files present contain the following:

• tweet_ids - A list of all tweets ids used in the study.
• coded_urls - A list of the (up to) five most common URLs from each of the 75 most common domains. Where these were not social media sites and content was available, they were graded for political and climate bias by the human coders.
• domain_bias_grades - A list of domains and the final bias scores assigned to them following the standardisation process we applied to the scores received from our coders. The first line of this file is a header labelling the four columns as political bias, climate change bias, political standard deviation and climate change deviation.

The networks folder contains subfolders for each of the seven weeks studied. Three files are provided for each week.

• week_x_bipartite_edges - A list of source, target pairs to define edges in the bipartite user-URL network. Source and target give the user and URL node IDs respectively. Pairs are not guaranteed to be unique, and duplicates should increment the edge weight.
• week_x_url_labels - A list of expanded URLs given in the order corresponding to the edge list described above.
• week_x_user_labels - A list of anonymised user IDs given in the order corresponding to the edge list for this week. These anonymised numeric user identifiers are consitent across each week for cross referencing.