Texturkartor

Texturkartor is a software framework and visualization environment designed for analyzing and mapping textual texture across corpora. It treats texture as the qualitative character of text—encompassing lexical variety, syntactic complexity, rhythm, coherence, discourse markers, and stylistic features—then maps these features onto geospatial or thematic canvases to reveal patterns of writing across time, region, author, or genre.

The project originated in digital humanities research in the late 2010s as a method to integrate content analysis with cartographic visualization. An early prototype was released in 2019 by a collaborative team from several universities, followed by a major update in 2021 that added multilingual analysis and a plug-in architecture. The platform is distributed as open-source software under a permissive license and can be deployed locally or accessed via hosted services.

Texturkartor's architecture is modular: core data ingestion and preprocessing, a suite of texture metrics (lexical density, syntactic complexity, narrative tempo, cohesion indices, sentiment proxies), and a visualization layer. The visualization includes texture heatmaps, atlas views for geotagged corpora, and interactive dispersion plots. It supports common data formats (JSON, CSV, XML) and integrates with NLP toolchains and GIS backends. A plugin API allows researchers to add metrics, visualizations, and data importers, enabling custom studies.

Applications span digital humanities, linguistics, journalism, and education. It is used to compare authorial styles, monitor stylistic variation across regions or outlets, and teach texture-based literary analysis. Critics note that texture remains partly interpretive and that results can be sensitive to metric definitions and data quality.