Russia has carried out attacks on several areas in Ukraine since February 2022. The war that has been going on for a long time has captured public attention, which is shown via Twitter. This study aims to determine the network in the communication of information dissemination related to the hashtag #UkraineRussiaWar on Twitter social media. This study uses the theory of Computer-Mediated Communication (CMC). Social Network Analysis (SNA) is a visualization method for understanding interaction patterns between individuals or communities and includes an overview of social networks according to the topics discussed. Social Network Analysis provides a means in the form of statistics used to examine relational data that focuses on explaining patterns of relationships between actors and analyzing the structure of network patterns using Gephi. This research used quantitative methods by applying Social Network Analysis with the Netlytic and Gephi models. Netlytic successfully recalled data from 2500 samples among active Twitter users. The results of the study show that there is betweenness centrality on the @blogukraine account with a value of 22.0 as the most substantial account in distributing information related to links, closeness centrality of 1,211 nodes which are popular actors in information distribution, and eigenvector centrality on the @militarylandnet account with a value of 1.0 as the most important actor in information dissemination and is continuously associated with related information. The war between Russia and Ukraine has become a protracted conflict and has broadly impacted the world. The visualization of SNA shows many responses from the world community via Twitter as a form of public concern for conflict resolution.
                        
                        
                        
                        
                            
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