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The rapid development of online social networks (OSNs) has facilitated people to express opinions and share information. To optimize the utility of information dissemination in OSNs, problems such as influence maximization have received increasing attention in recent years. However, not only positive information but also negative information is spreading in OSNs. The dissemination of positive and negative information interacts with each other, making network dissemination analysis and utility optimization more challenging. To this end, we develop a negative–neutral–positive–susceptible (NNPS) model and propose a max–min ant system algorithm with a repetitive influence reduction strategy (MMAS-RIR). First, an NNPS model with a novel heterogenous influence indicator is constructed to simulate the interactive dissemination of positive and negative information. The influence of each user’s neighbors on …