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I am working on topic modeling using the latent Dirichlet allocation model. I have a dataset that contains tweets and topics corresponding to these tweets. In total, there are 65 different topics. I applied the LDA model to tweets to find different topics in it. And now I have to find the accuracy of this model. The problem is I don't know how to find the accuracy of this model. I know there's a method called similarity score that can be used in some cases but I don't know how to apply that method here.

If there were a supervised model, I would compare the predicted output and actual output and know the accuracy. But in this case, I have no knowledge about it. Can anyone please explain to me how to find the accuracy of the LDA model?

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