Choosing the number of topics

So far, we have used a fixed number of topics, which is 100. This was purely an arbitrary number; we could have just as well done 20 or 200 topics. Fortunately, for many users, this number does not really matter. If you are going to only use the topics as an intermediate step as we did previously, the final behavior of the system is rarely very sensitive to the exact number of topics. This means that as long as you use enough topics, whether you use 100 topics or 200, the recommendations that result from the process will not be very different. One hundred is often a good number (while 20 is too few for a general collection of text documents). The same is true of setting the alpha (α) value. While playing around with it can change the topics, the final results are again robust against this change.

Tip

Topic modeling is often an end towards a goal. In that case, it is not always important exactly which parameters you choose. Different numbers of topics or values...