XSL Content

Language Technologies for Digital Humanities

General details of the subject

Face-to-face degree course

Description and contextualization of the subject

This course aims to understand in general terms the paradigm shift from Humanities to eHumanities or Digital Humanities (HD). Moreover, the student will try to create an interdisciplinary group to perform an HD project’s task using Natural Language Processing (PLN) tools or language technologies: helping and improving research results or re-assessing research. In order to do this, some use cases will be shown and the student’s work will follow the FAIR principles when he has to work with large amounts of data, visualization tools, methodologies and infrastructures, which can help to change the paradigm, decreasing the digital divide as much as possible. In addition, we will use (or create) language technologies to describe the textual complexity of known literary author, to enhance a richer use of language in language teaching and learning approach.


Demonstrate skills in working on an Humanities project in an interdisciplinary group, using natural language processing tools.30.0 %
Identify linguistic structures in text collections and tools for analysis in Humanities projects. 10.0 %
Ability to manage, enrich and handle language resources for human language processing.20.0 %
Ability to manage knowledge-based strategies and tools for human language processing.20.0 %
Develop action and communication skills in the digital context in order to develop an eHumanities project.20.0 %

Study types

TypeFace-to-face hoursNon face-to-face hoursTotal hours
Applied computer-based groups304575

Training activities

NameHoursPercentage of classroom teaching
Computer work practice, laboratory, site visits, field trips, external visits75.040 %
Lectures37.540 %

Assessment systems

NameMinimum weightingMaximum weighting
Attendance and participation10.0 % 10.0 %
OTROS10.0 % 10.0 %
Practical tasks30.0 % 30.0 %
Presentations20.0 % 20.0 %
Writing up the teamwork30.0 % 30.0 %

Learning outcomes of the subject

To know methods, tools, innovative projects in the Digital Humanities: (a) Projects that facilitate daily work in research, (b) to know how to improve your own research within DH projects and (c ) to know projects that only make sense in a digital context.

To learn to use language technologies to analyze and visualize textual data.

To know how to design an implementation of a multidisciplinary project in HD.

To identify methods, tools and resources of an DH project

To analyze text complexity using PLN tools.


1. Introduction to Digital Humanities and NLP.

2. DH infrastructures: tools, resources and services.

3. Data visualization techniques in DH.

4. Text and corpora processing.

5. Information representation and digital content management.

6. Analysis of textual complexity of literary texts to enhance a richer use of language.


Basic bibliography

Battershill, C., Ross, S. (2017). Using digital humanities in the classroom: A practical introduction for teachers, lecturers, and students. London: Bloomsbury Academic.

Dittrich, S., Weiss, Z., Schröter, H., & Meurers, D. (2019). Integrating large-scale web data and curated corpus data in a search engine supporting German literacy education. [Proceedings of the 8th Workshop on NLP for Computer-Assisted Language Learning (NLP4CALL)]. Linköping Electronic Conference Proceedings, 164, 41-56.

Schreibman, S., Siemens, R., Unsworth, J. (Eds.). (2004). A Companion to Digital Humanities. Oxford: Blackwell.

Otegi, A. Imaz, O. Díaz de Ilarraza, A. Iruskieta, M. Uria, L. (2017). ANALHITZA: a tool to extract linguistic information from large corpora in Humanities research. Procesamiento del Lenguaje Natural 58: 77-84.

Posner, M. (2013). How did they make that? Miriam Posner’s Blog, 29.

Sinclair, S., Rockwell, G. (2016). Voyant tools. URL: [September 5, 2016].