  With Twitter's growth and popularity, a huge number of views are shared by
users on various topics, making this platform a valuable information source on
various political, social, and economic issues. This paper investigates English
tweets on the Russia-Ukraine war to analyze trends reflecting users' opinions
and sentiments regarding the conflict. The tweets' positive and negative
sentiments are analyzed using a BERT-based model, and the time series
associated with the frequency of positive and negative tweets for various
countries is calculated. Then, we propose a method based on the neighborhood
average for modeling and clustering the time series of countries. The
clustering results provide valuable insight into public opinion regarding this
conflict. Among other things, we can mention the similar thoughts of users from
the United States, Canada, the United Kingdom, and most Western European
countries versus the shared views of Eastern European, Scandinavian, Asian, and
South American nations toward the conflict.
