DIGITAL HUMANITIES 2: CODING FOR SOCIAL SCIENCES AND HUMANITIES

The course will introduce the use of the R programming language, starting from a basic level and applying it to data related to Digital Humanities studies, in particular from cultural studies, from sociology and anthropology. During the course, the various steps to follow to develop a data analysis project will be presented, by making use of numerical data, text data, or graphical data. Theoretical aspects related to the functioning of the tools that are part of these steps will be explained and applied through the use of the R language. The course will highlight how programming might be fruitfully applied in Social Sciences and Digital Humanities research.

The students will be able to use the R programming language to critically analyze data related to Digital Humanities and Social Sciences, such as numerical data, text data and image data. At the end of the course, the students will be able to use R to perform quantitative data analysis and create reports presenting it.

There are no prerequisites required.

After an introduction about data analysis and algorithms, the course will cover the following topics:
- Basic R language
- Import data and its management
- Cleaning and tiding data
- Descriptive statistics
- Data visualization
- Analysis of images
- Analysis of maps
- R markdown

Selected articles will be proposed during the course, shared on Moodle

Additional books and manuals (optional):
H. Wickham and G. Grolemund, “R for data science”, O’Reilly Media, 2016 (https://r4ds.had.co.nz )
C. Chapman and E. McDonnell Feit, “R for Marketing Research and Analytics”, Springer, 2015
T. Arnold and L. Tilton, “Humanities data in R. Exploring networks, geospatial data, images, and text” Springer, 2015

The assessment will consist of a test after the first half of the course (20% of the final mark) and in the development of a final project, realized using the R language, to be presented in class (70% of the final mark). Class participation will account for 10% of the final mark.

The lessons will be frontal. During the course, the R programming language will be presented and then actively used by, and discussed with, the students.

written and oral