texstan

texstan is a system for analyzing the statistical properties of text. It was developed to help researchers understand patterns in language use, identify authorship, and detect plagiarism. The core functionality of texstan involves generating various statistical measures from a given text corpus. These measures can include word frequencies, sentence lengths, the distribution of specific n-grams (sequences of words), and measures of lexical diversity.

The system is designed to be flexible, allowing users to customize the analysis by selecting which statistical features to extract. It can handle large amounts of text data and provides output in formats that are easily usable for further statistical modeling or machine learning tasks. Applications of texstan range from forensic linguistics, where it can aid in identifying authors of anonymous texts, to literary analysis, where it can help characterize the style of different authors or periods.

texstan is also used in computational linguistics research to explore hypotheses about language structure and evolution. Its ability to quantify textual features makes it a valuable tool for researchers looking to move beyond purely qualitative interpretations of text. The development of texstan aims to provide a robust and accessible platform for statistical text analysis, contributing to a more data-driven approach in fields that rely heavily on textual evidence.