/Foundations-of-Cultural-and-Social-Data-Analysis

UvA - Foundations of Cultural and Social Data Analysis

Primary LanguageJupyter NotebookGNU General Public License v3.0GPL-3.0

University of Amsterdam (UvA) - Foundations of Cultural and Social Data Analysis

Open In Colab

In this course, students have an introduction to Python so that they can conduct initial analysis on socio-cultural phenonena using data. Socio-cultural data pose great challenges and offer many opportunities due to their variety and richness, such as historical and literary sources, online social networks and media. During this course, students are introduced to the foundation concepts and techniques for analyzing such a variety of data.

You can run all the notebooks for this course using Colab (link above). If you prefer to work locally, I recommend using Jupyter notebooks which are easily accessible using the Anaconda interface.

Syllabus

Week Topic Materials
0 Preparation (Giovanni Colavizza's Material) notebook
1 Introduction (Giovanni Colavizza's Material) slides + notebook
2 Data Gathering and Cleaning + Foundation of Statistics slides + notebook
3 Data Analysis: Exploring your data slides + notebook
4 Combining Data slides + notebook
5 Visualizing Data slides

Datasets

The datasets used in this course can be found here.

Students can also use these datasets(https://github.com/mromanello/ADA-DHOxSS/tree/master/data) to test their knowledge. They are from the Applied Data Analysis course.

Assignments

See the assignments folder.

Readings

A good companion for this course is John Canning, Statistics for the Humanities, 2014. Also recommended are Melanie Walsh, Introduction to Cultural Analytics & Python, 2021 and Karsdorp, Kestemont, Riddell, Humanities Data Analysis: Case Studies with Python, 2021.

Author

Mathias-Felipe de-Lima-Santos (Ph.D.) is a postdoctoral researcher in the Human(e) AI project at the University of Amsterdam, Netherlands. He is also a faculty associate in the Digital Media and Society Observatory (DMSO) at the Federal University of São Paulo (Unifesp), Brazil. Previously, he was a researcher at the University of Navarra, Spain, under the JOLT project, a Marie Skłodowska-Curie European Training Network funded by the European Commission’s Horizon 2020. He was also a Visiting Researcher at the Queensland University of Technology (QUT) in Brisbane, Australia. Mathias-Felipe is co-editor of the book “Journalism, Data, and Technology in Latin America” published by Palgrave Macmillan in 2021. His research interests include the changing nature of communications driven by technological innovations, particularly in journalism, media, and online social networks.

License

Everything in this repository which is not already attributed to someone else is released under CC BY 4.0.