The fight against disinformation and its consequences: measuring the impact of “Russia state-affiliated media” on Twitter

Abstract

On February 28th, shortly after the Russian invasion of Ukraine on February 24th, Twitter announced the expansion of its labelling policy for “Russia state-affiliated media”, in order to address disinformation in favour of the Russian government. While this ‘soft’ approach does not include the removal of content, it entails issues for freedom of expression and information. This article investigates the consequences of this labelling policy for the range and impact of accounts labelled “Russia state-affiliated media” during the Ukrainian war. Using an iterative detection method, a total of 90 accounts of both media outlets and individual journalists with this label were identified. The analysis of these accounts’ information and timeline, as well as the comparison of the impact of their tweets before and after February 28th with an ARIMA model, strongly suggests, that this policy, despite its limited scope, could have contributed to a reduction in the impact of the sampled tweets, among other concurrent events. These results provide empirical evidence to guide critical reflection on this content moderation policy.