The Verifying Multimedia Use task aims to detect misuse of online multimedia content and verify them as real or fake. This is a highly challenging problem because of strong variations among tweets from different events. Traditional approaches train the classifier at message level, which ignores inter-message relations. We propose a two-level classification model to exploit the information that tweets of a same topic are probably have same credibility values. In this model a topic level is

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... uced to eliminate message variations. Messages are aggregated into topics as a higher level representation. Pre-results gained from classification at the topic level are then fused with original message level features to train a better classifier. Results indicate that topic level is very helpful and our two-level approach offers significantly better results than a traditional one-level method. Our best result on this task achieves an F-score of 0.94 using features extracted only from tweet content.