Authors

Discussion

The emergence of social media platforms has radically transformed how individuals and societies engage in memory activism. By accelerating the creation and spread of memory-related content, social media enable new possibilities for challenging different forms of present (and historical) injustice and bringing hope for a better future. However, the effective mobilization enabled via digitally mediated references to the past is also used by today's repressive regimes and their activists to propagate their own hopes and expectations, including future imaginaries of (ideological) oppression and violence.

Russia's war against Ukraine, which has been escalated by the Kremlin in 2022, has been associated with different forms of pro- and anti-war memory activism. These activists are often influencers and opinion leaders, identifiable by their high levels of engagement in the online sphere, including significant numbers of likes, views, and network-wide engagement. The Kremlin actively relied on it for constructing negative identities of Ukrainians and inciting violence since 2014; by contrast, anti-regime activists, many also with considerable influence online, referred to the past to ignite the hope of the regime being undermined by its aggressive foreign politics. However, a systematic investigation of the evolution of these different forms of pro- and anti-war memory activism and their relationship with hopes is currently lacking; similarly, there is a limited understanding of how such memory activism may be shaped by different social media platform affordances and communication practices.

To address these gaps, we rely on a large set of cross-platform data regarding several key personalities from  20th-century Soviet and Russian history. Data were collected via social media listening and captured mentions of Stalin, Lenin, Yeltsin, Gorbachev from 30 December 2021 to 15 March 2022 on VK, Instagram, X, Facebook, and Odnoklassniki. We use dynamic topic modelling based on Bertopic, a state-of-the-art natural language processing technique, to identify the evolution of distinct issues related to memory activism before and after the full-scale invasion.