Module overview
In this module, you will explore one of the primary forms of data used in humanities data science - text! You will develop an understanding of text as a form of data, including what can (and can't!) be do with it. You will explore and compare varying aproaches to collecting and analysing text as data. Ultimately, you will design and deliver a project that situates the use of text as data in a humanities research context.
Aims and Objectives
Learning Outcomes
Knowledge and Understanding
Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:
- Methodological and theoretical underpinnings of different approaches to text analysis
- Methods for designing, developing, and analysing large-scale text data
- Quantitative and statistical measures in large-scale text analysis
Subject Specific Practical Skills
Having successfully completed this module you will be able to:
- apply the of use general and specialist software for large-scale text analysis, management, and visualisation
- perform practical text analysis techniques that are informed by environmental and social justice principles within professional, legal, and ethical frameworks
Subject Specific Intellectual and Research Skills
Having successfully completed this module you will be able to:
- critically evaluate the uses, advantages, and disadvantages of using text analysis methods
- apply text analysis methods and techniques to primary data analysis
- justify methodological choices in text data collection, curation and analysis
Transferable and Generic Skills
Having successfully completed this module you will be able to:
- critically evaluate and justify choices made throughout the research process
- exercise self-direction and originality in planning and delivering a data-driven research project
- effectively apply a range of communication techniques to engage a diverse and interdisciplinary audience
Syllabus
Indicative content include:
- Text, its forms, and its functions as data
- Statistical measures in text analysis
- Collecting and curating text data for humanities research
- Annotating and pre-processing text data
- Using specialist and generic software for text analysis
- Visualising and presenting findings from text analysis
Learning and Teaching
Teaching and learning methods
Teaching and learning activities will take the form of active workshops, where students work in groups to develop experiential understanding of all aspects of large-scale text analysis research. This will variably include – inter alia – working through research problems in active discussion (e.g. what data do we need to answer research question X?), analysing data and presenting findings (e.g. how has the use of X changed over time in the British National Corpus?), and/or critiquing existing research using text analysis methods (e.g. in light of the aims of this study, what would you do differently and why?).
This module places explicit emphasis on the development of practical skills for working with data, using specialist software, and justifying choices made in the research process. A collaborative ethos is also embedded in the teaching and learning experience, which is also supported in asynchronous activities via the virtual learning environment.
| Type | Hours |
|---|---|
| Independent Study | 114 |
| Seminar | 36 |
| Total study time | 150 |
Assessment
Summative
This is how we’ll formally assess what you have learned in this module.
| Method | Percentage contribution |
|---|---|
| Final project | 80% |
| Project plan | 20% |
Referral
This is how we’ll assess you if you don’t meet the criteria to pass this module.
| Method | Percentage contribution |
|---|---|
| Final project | 100% |
Repeat
An internal repeat is where you take all of your modules again, including any you passed. An external repeat is where you only re-take the modules you failed.
| Method | Percentage contribution |
|---|---|
| Final project | 100% |