AJL14157 R for Students of Literature

Filozofická fakulta
jaro 2021
Rozsah
0/2/0. 6 kr. Ukončení: zk.
Vyučující
Mgr. Stefan Veleski, B.A., Ph.D. (přednášející)
Garance
Stephen Paul Hardy, Ph.D.
Katedra anglistiky a amerikanistiky – Filozofická fakulta
Kontaktní osoba: Tomáš Hanzálek
Dodavatelské pracoviště: Katedra anglistiky a amerikanistiky – Filozofická fakulta
Rozvrh
Čt 18:00–19:40 D41
Předpoklady
AJL01002 Anglický jazyk II || AJ01002 Anglický jazyk II
Omezení zápisu do předmětu
Předmět je nabízen i studentům mimo mateřské obory.
Předmět si smí zapsat nejvýše 20 stud.
Momentální stav registrace a zápisu: zapsáno: 0/20, pouze zareg.: 0/20, pouze zareg. s předností (mateřské obory): 0/20
Mateřské obory/plány
předmět má 11 mateřských oborů, zobrazit
Cíle předmětu
This course aims to introduce students to the R programming language. The course is intended to give students a gentle push towards the path of programming, which may either take them towards a more data driven approach in their MA studies, or towards careers that mix insight from the humanities and programming and/or data analysis, such as technical writing. By the end of the course, the students will be acquainted with the fundamentals of R, version control with Github, the basics of computational analysis of text, R Markdown as a markup language, and how to create a website in R Studio with the "blogdown" package. Moreover, the students will begin to think about the application of quantitative approaches to the study of literature and will acquire the necessary knowledge to continue independent work and further develop their programming skills according to their academic or professional needs.
Výstupy z učení
By the end of the course, the student will be acquainted with:
- The basics of R, objects, data types;
- The most common functions, subsetting;
- Loops, for loops, apply family of loop functions;
- Using R in for analyzing tabular data — "tidyverse" collection of packages;
- Word frequency and token distribution analysis;
- Sentiment analysis ("syuzhet" and "sentimentr" packages);
- Topic modeling;
- Version control with Github;
- R Markdown (markup and documentation);
- "Blogdown" package (making a website in R Studio).
Literatura
    povinná literatura
  • SILGE, Julia a David ROBINSON. Text mining with R : a tidy approach. First edition. Boston: O'Reilly, 2017, xii, 178. ISBN 9781491981658. info
  • WICKHAM, Hadley a Garrett GROLEMUND. R for data science : import, tidy, transform, visualize, and model data. First edition. Sebastopol, CA: O'Reilly, 2016, xxv, 492. ISBN 9781491910399. info
  • PENG, Roger D. R Programming for Data Science. Leanpub, 2015, 182 s. info
  • JOCKERS, Matthew Lee. Text analysis with R for students of literature. Cham: Springer, 2014, xvi, 194. ISBN 9783319349190. info
Metody hodnocení
Grades will be based on the following percentages:
Class Participation 10%
Quizzes (2) 10%
Assignments (3) 30%
Final Project 50%

The quizzes are aimed at testing the practical knowledge of R and tidyverse functionality and will be concentrated in the early stages of the course. The assignments will consist of certain problems that will require critical thinking and applying the skills acquired in the first five weeks of the course. The final project will be a small research project (5-6 pages including the sources and visualizations) that should be sent to me as an R Markdown PDF file at the end of the semester. Students can choose any of the techniques covered in the course, and apply them on a topic of their choosing. This should be discussed with me in advance, in order to ensure feasibility of the study and availability of the data.

Letter grade distribution: ≤59 F, 60-69 E, 70-75 D, 76-79 C, 80-85 B, >= 86 A
Vyučovací jazyk
Angličtina
  • Statistika zápisu (nejnovější)
  • Permalink: https://is.muni.cz/predmet/phil/jaro2021/AJL14157