a Python implementation of different measures of distinctiveness for contrastive text analysis


Project Management: Prof Dr Christof Schöch  (Universität Trier - Computerlinguistik & Digital HumanitiesUniversität Trier - Trier Center for Digital Humanities (TCDH)) · Universität Trier - Trier Center for Digital Humanities (TCDH)

Sponsors: Deutsche Forschungsgemeinschaft (DFG)

Running time: -

Contact person (TCDH): Prof Dr Christof Schöch


pydistinto. Lead & development: Christof Schöch, Keli Du. Trier: Zeta and company, 2021-2023. URL: (Vormals pyzeta).

Research Area: Digital Literary and Cultural Studies

Keywords: Digital Technologies and Tools, Text Mining


Website of the Project: github

As part of the project "Zeta und Konsorten", the tool "pydistinto" could be developed and presented at various professional conferences. The team is developing the research-oriented tool, written in Python, to facilitate the use and evaluation of relevant measures for contrastive text analysis. The goal of our project is to gain a deeper qualitative and statistical understanding of the various distinctiveness measures and to propose improvements for their implementation and use. The tool renews the pyzeta code base from a previous project.

Related projects: Zeta and Company


Iuliia Dudar
E-mail: dudaratuni-trier [dot] de

Keli Du
E-mail: dukatuni-trier [dot] de
Phone: +49 651 201-3377

Prof Dr Christof Schöch
E-mail: schoechatuni-trier [dot] de
Phone: +49 651 201-3264