Abstract
Social media provides users with a platform for information sharing and communication. At the same time, there are a large proportion of users use a fake avatar. We attempt to automatically discriminate the authenticity of the user’s uploaded person avatar based on the machine learning method. In this paper, an avatar authenticity discrimination method based on multi-feature fusion is proposed by combining user-based features, avatar features, and text-based features. We use deep learning, image recognition and topic model techniques to process features. The method is verified on the Sina Weibo data set. The experimental results show that the method can achieve 84.1% accuracy.
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