Análise do posicionamento político dos brasileiros em relação à guerra Irã x EUA utilizando dados do YouTube

Abstract

The growing volume of data produced on social networks has expanded the possibilities for investigating sociopolitical phenomena and public opinion behavior. This study aims to analyze the positioning of Brazilians regarding the war between the United States and Iran using comments extracted from YouTube. The methodology involved collecting 14,052 comments from videos related to the topic, followed by automated labeling of the texts regarding their stance (pro, against, or neutral to the war) and the supported side (US or Iran) using the Gemini 3.1 Pro large language model. For the structural analysis of the discussions, the data was modeled as undirected and weighted complex networks, whose edges represent lexical similarity between comments, projected from a bipartite comment-term structure. The application of centrality metrics (Degree, Betweenness, Closeness, and PageRank) identified a small core of comments that exert strong structural influence on the discussions. Additionally, the Girvan-Newman algorithm detected the formation of 10 distinct communities, revealing blocks of discourse with shared themes and vocabularies. The results demonstrate the effectiveness of combining text mining techniques and complex network theory to map and interpret spontaneous user manifestations, showing that relational structures can assist in identifying opinion patterns in digital political debate.