The explosion of the Web leads to the production of large amounts of texts and inevitably influences their quality. Errors that tend to occur more often can distort results, especially when texts are used for scientific purposes, in language teaching or learning. Hence, there is a need to examine the existing corpora based on web texts and to clean up the data, which may contain such "noisy"fragments. In our study, we deal with the problem of errors and analyze the Aranea Russicum Maximum corpus. Among such errors, we can name, above all, encoding errors, incorrect font types, as well as segments written in other languages. These phenomena result in incorrect morphological analysis and lemmatization, frequency distortion, as well as the fact that lexical units cannot be found and therefore displayed to corpus users. The paper focuses on the errors, describes their types and outlines possible ways to eliminate them.