nireEHU 
Subject
Language Technologies for Digital Humanities
General details of the subject
- Mode
- Face-to-face degree course
- Language
- English
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.Teaching staff
| Name | Institution | Category | Doctor | Teaching profile | Area | |
|---|---|---|---|---|---|---|
| ALTUNA DIAZ, BEGOÑA | University of the Basque Country | Doctor | Bilingual | ** n o c o n s t a e l a r e a * ó " á r e a p r o v i s i o n a l" | begona.altuna@ehu.eus | |
| IRUSKIETA QUINTIAN, MIKEL | University of the Basque Country | Profesorado Agregado | Doctor | Bilingual | Teaching of Language and Literature | mikel.iruskieta@ehu.eus |
| MEURERS , WALT DETMAR | Universität Tübingen | Doctor |
Competencies
| Name | Weight |
|---|---|
| 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
| Type | Face-to-face hours | Non face-to-face hours | Total hours |
|---|---|---|---|
| Lecture-based | 15 | 22.5 | 37.5 |
| Applied computer-based groups | 30 | 45 | 75 |
Training activities
| Name | Hours | Percentage of classroom teaching |
|---|---|---|
| Computer work practice, laboratory, site visits, field trips, external visits | 75.0 | 40 % |
| Lectures | 37.5 | 40 % |
Assessment systems
| Name | Minimum weighting | Maximum weighting |
|---|---|---|
| Attendance and participation | 10.0 % | 10.0 % |
| OTROS | 10.0 % | 10.0 % |
| Practical tasks | 30.0 % | 30.0 % |
| Presentations | 20.0 % | 20.0 % |
| Writing up the teamwork | 30.0 % | 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.
Temary
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.
Bibliography
Basic bibliography
Battershill, C., Ross, S. (2017). Using digital humanities in the classroom: A practical introduction for teachers, lecturers, and students. London: Bloomsbury Academic. https://ehu.on.worldcat.org/oclc/7177087005Dittrich, 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. https://ep.liu.se/ecp/164/005/ecp19164005.pdf
Schreibman, S., Siemens, R., Unsworth, J. (Eds.). (2004). A Companion to Digital Humanities. Oxford: Blackwell. http://www.digitalhumanities.org/companion/
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. https://miriamposner.com/blog/how-did-they-make-that/
Sinclair, S., Rockwell, G. (2016). Voyant tools. URL: https://voyant-tools.org/ [September 5, 2016].