In this paper, we analyze a dataset including more than 189 million tweets related to the first month of the 2022 war in Ukraine. Our analysis especially focuses on communities of Twitter users and their collective behavior. In particular, we applied the InfoMap community detection algorithm and found on average 44079.63 communities of Twitter users per day. Our behavioral analysis especially focuses on the five largest daily communities (i.e. the communities that have been detected for each day during the first month of the war). We found that: 1) hashtags played an essential role in framing conversations, 2) communities often publicly called on international organizations or offices such as @potus, @NATO, or @UN to aid in conflict resolution, 3) anger was the dominant emotion in all communities and 4) negative tweets spread wider than the positive ones.

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