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A LGBTfobia no ambiente digital tem sido investigada predominantemente em plataformas abertas, onde interações explícitas facilitam a modelagem de redes. Em aplicativos de mensageria instantânea, contudo, a circulação de conteúdos ocorre de forma mais opaca, exigindo estratégias específicas de análise. Este trabalho propõe um método para modelar a dinâmica do compartilhamento de mensagens LGBTfóbicas no WhatsApp e no Telegram por meio de redes de co-compartilhamento. Utilizamos o dicionário PrejudicePT-br para selecionar as mensagens de interesse e construímos uma rede usuário--usuário com arestas ponderadas indicando o co-compartilhamento de mensagens idênticas. A estrutura resultante foi avaliada por meio de medidas globais, componentes conexas e detecção de comunidades, complementadas por uma análise qualitativa que distingue gatilhos lexicais ambíguos de termos pejorativos explícitos. Os resultados revelam um padrão global fragmentado, com um núcleo coeso sustentado por um conjunto reduzido de mensagens. O estudo oferece um pipeline replicável e evidências empíricas sobre a estrutura da circulação de conteúdo LGBTfóbico em aplicativos de mensageria instantânea.

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LGBTphobia in the digital environment has predominantly been investigated on open platforms, where explicit interactions facilitate network modeling. On instant messaging apps, however, content circulation occurs more opaquely, requiring specific analysis strategies. This paper proposes a method to model the dynamics of sharing LGBTphobic messages on WhatsApp and Telegram using co-sharing networks. We used the PrejudicePT-br dictionary to select messages of interest and constructed a user-to-user network with weighted edges indicating the co-sharing of identical messages. The resulting structure was evaluated using global metrics, connected components, and community detection, complemented by a qualitative analysis distinguishing ambiguous lexical triggers from explicit pejorative terms. The results reveal a fragmented global pattern, featuring a cohesive core sustained by a small set of messages. The study offers a replicable pipeline and empirical evidence regarding the structure of LGBTphobic content circulation on instant messaging apps.

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#	Name
1	Fernanda Nascimento(nascimentofernandaf@outlook.com)
2	José Monteiro(jose.monteiro@lsbd.ufc.br)
3	Javam Machado(javam.machado@lsbd.ufc.br)

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