Research project SWEGRAM – A Tool for Text Analysis for Swedish and English
Empower Your Text Analysis: Annotate and Analyze Swedish and English Texts with SWEGRAM
SWEGRAM aims to provide a tool for text analysis in Swedish and English. Users can upload one or multiple texts and annotate them at various linguistic levels with morphological and syntactic information. The annotated texts can then be used to extract statistics pertaining to text properties such as text length, word count, readability measures, part-of-speech, syntactic features, and much more.
Users have the option to download the annotated data along with the statistics for the uploaded files. The data can be saved in formats such as plain text, CSV, or Excel files. Additionally, users can continue building their annotated corpus using the tool.
The tool has two versions:
A downloadable desktop version with an extended feature set:
An online first version (which is not maintained anymore):
When you use SWEGRAM in your work, please refer to the following publications:
SWEGRAM – Annotering och analys av svenska texter (3746 Kb)
(2019)
SWEGRAM – A Web-Based Tool for Automatic Annotation and Analysis of Swedish Texts (272 Kb)
(2017)
Please find complete info and links under Publications on this site.
Project members
Project managers
Beata Megyesi
Professor
Members
Anne Palmér
Associate Professor
Publications
More about this project
The first version of the SWEGRAM tool resulted from a collaboration between the Department of Linguistics and Philology and the Department of Scandinavian Languages at Uppsala University. Subsequently, the second version of the tool was developed by the Department of Linguistics at Stockholm University. Funding for the tool's development was provided by the SWE-CLARIN project, which aims to create linguistic data and tools for researchers in the Humanities and Social Sciences through the utilization of sophisticated text and speech processing tools.
System developers in the project
SWEGRAM has been developed in cooperation with three system developers:
Rex Ruan (2019- )
Shifei Chen (2019-2021)
Jesper Näsman (2016-2018)
We express our gratitude to Eva Pettersson and the master’s students enrolled in the Language Technology Program at Uppsala University from 2018 to 2021, for their valuable input on various aspects of the tool.