In this paper a four component analysis method is proposed for analysing political communication patterns over Social Media. The method is applied over Twitter content relevant to the Russo-Ukrainian war, mined over the first trimester that followed the Russian invasion of Ukraine on the 24h of February 2022. More specifically, data was mined from a sample of thirty high-profile Twitter accounts, fifteen affiliated with each conflicting part. The four components of the proposed method were Tweet statistics, Text Analysis, Sentiment Analysis and Network Analysis. This research was implemented using exclusively open-source software and aimed in identifying the characteristics of the two groups’ overall strategy, tweeting “reach” metrics, text usage, coordination, and induced sentiment. Subsequently, a post-processed data network analysis highlighted the important profiles that emerged via their interactions in their mutual network where the main coalitions were visually presented. The results of the analysis using the proposed multidimensional method confirmed the literary view that the Ukraine’s distinct Social Media strategy was comparatively more effective, a fact that proved to be based on achieving higher “reach” metrics in Twitter, inducing positive sentiment with carefully tailored diffused messages under a certain degree of coordination and by establishing a beneficial coalition digital network with other countries and institutions.