Visualizing Humanities and Social Analytics
Vrije Universiteit Amsterdam
Amsterdam, The Netherlands
Area of Study
Information Technologies, Sociology
Taught In English
Course Level Recommendations
ISA offers course level recommendations in an effort to facilitate the determination of course levels by credential evaluators.We advice each institution to have their own credentials evaluator make the final decision regrading course levels.
Recommended U.S. Semester Credits3
Recommended U.S. Quarter Units4
Hours & Credits
• Students will become familiar with the methods, concepts and practices of data visualization in Digital Humanities and Social Analytics
• Students will learn to critically reflect on the implications of the selection, structuring and manipulation of data as well as the choice of visualization techniques to present the outcomes of research projects.
• Students acquire practical skills in data visualization techniques including the quantitative analysis of textual data (e.g. (social) media data) through AmCAT and R.
• Students will learn to apply their knowledge and skills by developing their own research projects around a given dataset, formulate relevant questions and use visualizations for their analysis.
• Students will be able to position their own work in the field of Digital Humanities and Social Analytics.
• Students will learn to collaborate in an interdisciplinary group, manage group processes, and communicate their results to an audience of peers and teachers.
This course will offer analytical and practical training in digital visualization techniques, placed in the broader scope of Digital Humanities and Social Analytics. In terms of critical reflection and theory this is a more advanced course within the Minor Digital Humanities and Social Analytics. Visualization of data plays an important role in exploring and analysing quantitative data deriving from large and complex datasets, such as relational databases and text corpora varying from 17th century literature to newspaper archives to tweets.
Visualizations can be used both to present the end results of research projects as well as to support all phases of the hermeneutic cycle of questioning, searching, aggregating and analysing data. They may reveal patterns and provide leads for new research questions. In this course students will become familiar with visualizations in R and learn to reflect critically on the way they can be used.
An important part of the classes will entail practical training in the processing of data. You may use the dataset you worked on in the course ‘From Object to Data’. This course invites you to develop your own research around a topic of your choice. The visualization of textual data will help you to manage and analyse large corpora of texts. You will define and investigate a research question, learn how to structure data and how to uncover patterns in your data through visualization. At the end of the course you will be able to use attractive visualizations to present your research results in both oral and written communications.
Seminar, 2 x 2 hours / week
TYPE OF ASSESSMENT
Participation, assignments and presentation (40%), research paper (60%)
Courses and course hours of instruction are subject to change.
Some courses may require additional fees.