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This article attempts to address the opinion target classification of microblog comments through an event graph convolution network (EventGCN) in a weak-supervised manner. Specifically, we take microblog contents and comments as document nodes, and construct an event graph with three typical relationships of event microblogs, including the co-occurrence relationship of event keywords extracted from microblogs, the reply relationship of comments, and the document similarity. Finally, under the supervision of a small number of labels, both word features and comment features can be represented well to complete the classification. 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