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In this paper we present a multimodal approach to categorizing user posts based on their discussion topic. To integrate heterogeneous information extracted from the posts, i.e. text, visual content and the information about user interactions with the online platform, we deploy graph convolutional networks that were recently proven effective in classification tasks on knowledge graphs. As the case study we use the analysis of violent online political extremism content, a challenging task due todoi:10.1145/3126686.3126776 dblp:conf/mm/RudinacGW17 fatcat:kxpmaws5yzeovijqlg57rsd3xe