DOI: 10.5281/zenodo.12754897
title: Extinction Rebellion Finland (Elokapina) Post-Repression Twitter Activity and Network Patterns

description: Overview

This repository contains two time series data sets of activity levels and network patterns on Finnish climate Twitter for the period of July 18, 2020 to February 11, 2022. First, there is a day-level data set (574 days) containing Twitter activity levels of climate activists and non-activists. Second, there is a week-level data set (81 weeks) containing estimated coefficients for various network effects from exponential random graph models (ERGM) fit to retweet networks.

For details, including definitions of activist/non-activist and the ERGM specifications, please see the referenced work: "Social Media Affordances Sustain Social Movements Facing Repression: Evidence from Climate Activism", detailed below.

 

Data Set Details

`raw_daily_counts.csv` contains the following variables at the day level.



date: from 2020-07-25 to 2022-02-11

activity_activist: the daily activity count of activist users on Finnish climate Twitter

activity_nonactivist: the daily activity count of non-activist users on Finnish climate Twitter

users_activist: the daily count of activist users on Finnish climate Twitter

users_nonactivist: the daily count of non-activist users on Finnish climate Twitter


`weekly_ERGM_coefficients.csv` contains a subset of estimated coefficients from ERGMs of weekly retweet networks from Finnish climate Twitter. The data set contains the following variables (coefficients), not all of which are from the same model specification.



week: starting with week 2 (2020-07-25 to 2020-07-31) and ending with week 82 (2022-02-05 to 2022-02-11)

political_activity_activist: activists retweeting politically relevant users

political_activity_nonactivist: non-activists retweeting politically relevant users

gwidegree0_activist: geometrically weighted in-degree (decay = 0) for the activist subnetwork

gwidegree0_nonactivist: geometrically weighted in-degree (decay = 0) for the non-activist subnetwork

gwidegree0_activistsub_thresh3: geometrically weighted in-degree (decay = 0) for the activist subnetwork with an activity level requirement for activists

gwidegree0_activistsub_thresh4: geometrically weighted in-degree (decay = 0) for the activist subnetwork with an activity level requirement for activists

gwidegree0_activistsub_thresh5: geometrically weighted in-degree (decay = 0) for the activist subnetwork with an activity level requirement for activists

gwidegree0_activistsub_thresh6: geometrically weighted in-degree (decay = 0) for the activist subnetwork with an activity level requirement for activists

gwidegree0_activistsub_thresh7: geometrically weighted in-degree (decay = 0) for the activist subnetwork with an activity level requirement for activists

gwidegree0_activistsub_thresh8: geometrically weighted in-degree (decay = 0) for the activist subnetwork with an activity level requirement for activists

gwidegree0_activistsub_thresh9: geometrically weighted in-degree (decay = 0) for the activist subnetwork with an activity level requirement for activists


 

References

Please reference the original study when using this data set.Savolainen, Sonja, Ville P. Saarinen, and Ted Hsuan Yun Chen. 2024. “Social Media Affordances Sustain Social Movements Facing Repression: Evidence from Climate Activism.” doi:10.31235/osf.io/p4yvk.