  The number of topics might be the most important parameter of a topic model.
The topic modelling community has developed a set of various procedures to
estimate the number of topics in a dataset, but there has not yet been a
sufficiently complete comparison of existing practices. This study attempts to
partially fill this gap by investigating the performance of various methods
applied to several topic models on a number of publicly available corpora.
Further analysis demonstrates that intrinsic methods are far from being
reliable and accurate tools. The number of topics is shown to be a method- and
a model-dependent quantity, as opposed to being an absolute property of a
particular corpus. We conclude that other methods for dealing with this problem
should be developed and suggest some promising directions for further research.
