To evaluate and understand the dynamics of citizen participation in social networks concerning the war in Ukraine and delve into the phenomenon of cyberactivism, this study focuses on the conversation generated in Spanish around the conflict on Twitter. The research analyses 1,138,747 original tweets to investigate the general characteristics of the conversation, the user interaction patterns, and the creation and structure of communities and to determine the connecting factors. The study employs machine learning and artificial intelligence techniques via the Graphext data analytics tool. The conversation volume is very high, but the network of interactions is characterized by being unstructured and dominated by white noise, with disjointed interactions setting the tone of the conversation. Verified accounts and emotionality stand out as factors of connection and interconnection in the network. This case study highlights a form of social and political participation oriented towards visibility and information about the cause at a level of deliberation and debate that shows empathy and sympathy in a context close to slacktivism.