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Online social networks have greatly facilitated the dissemination of information. The study of influence maximization(IM) in social networks is an important field. IM aims to find a subset of nodes with the maximum spreading influence. However, traditional research on IM ignores the reliability of data. Due to the uncertainty of data, there is a requirement to ensure connections between network nodes in IM are reliable. To solve this problem, this paper proposes a network embedding prediction model to analyze data reliability and an improved ant colony algorithm for IM. First, we predict the true connections between network nodes through the network embedding prediction model. EA - NEcornrnunity network embedding is used to represent the connections obtained from unreliable data by vectors. Based on these vectors, back-propagation neural network predicts the true connectivity relationships. Second, we …