Updating One-Hot Encoding to account for new categories
I think you have two options:


Automate your train/test pipeline so that one-hot encoding is part of
it. If new categorical variables are introduced, they can be featured
in the training dataset even if not very prevalent. This would
introduce some bias if the nature of the TV show distribution has
changed over time (e.g. 20 years ago there weren't as many options)
but I don't necessarily think it is a show stopper.
If new possibilities are introduced over time but for whatever reason you can't  retrain, then you should omit using that new value. This has its own disadvantages because in your example, it would be a TV show with no network.