  Stop words are very important for information retrieval and text analysis
investigation tasks of natural language processing. Current work presents a
method to evaluate the quality of a list of stop words aimed at automatically
creating techniques. Although the method proposed in this paper was tested on
an automatically-generated list of stop words for the Uzbek language, it can
be, with some modifications, applied to similar languages either from the same
family or the ones that have an agglutinative nature. Since the Uzbek language
belongs to the family of agglutinative languages, it can be explained that the
automatic detection of stop words in the language is a more complex process
than in inflected languages. Moreover, we integrated our previous work on stop
words detection in the example of the "School corpus" by investigating how to
automatically analyse the detection of stop words in Uzbek texts. This work is
devoted to answering whether there is a good way of evaluating available stop
words for Uzbek texts, or whether it is possible to determine what part of the
Uzbek sentence contains the majority of the stop words by studying the
numerical characteristics of the probability of unique words. The results show
acceptable accuracy of the stop words lists.
