LDA topic model has 0-weight topics, is that normal?
It's normal: LDA tries to maximize the likelihood of the data according to the parameters by finding the right probabilities for the parameters. Usually at the beginning increasing the number of topics allows the model to separate topics more precisely and therefore obtain a higher likelihood. But at some point (depending on the data), increasing the number of topics cannot help the model anymore because the topics are already separated to the maximum and using all the topics would actually decrease the likelihood.
So it's a sign that you don't need that many topics. Note that it doesn't mean that the number of &quot;used&quot; topics is optimal for the application, it's often a balance to find.