(in Polish) Introduction to Computational Social Science 3700-MSNS-ICSS-ALL
The development of the Internet and social media opens a whole new world of possibilities for social scientists to track human behavior. The questions that were difficult to handle using traditional methods of data collection and analysis can now be addressed. Furthermore, the new possibilities allow for the formulation of new questions and tracking phenomena, which were impossible to follow before. However, the new sources of information require social scientists to work on the verge of social science and computer science. This new area is usually called computational social science. Therefore, social scientists need to learn what type of data is available out there, how to collect it, and how to analyze it. It does not necessarily mean that they need to learn computer science because they might cooperate with computer scientists, but at least they need to understand the basic concepts to be able to plan adequate research.
This course is an introduction to computational methods for social scientists, therefore, it will introduce basic concepts only. It will not cover advanced methods, techniques, and theories. During the course, the following topics will be introduced: available data sources, Natural Language Processing (NLP), network analysis, and computer simulations. However, the focus will be not on the technical aspect but on the possible applications for social scientists. Each topic will be illustrated with real-life examples.
At the end of the course, students will be able to understand basic concepts of computational social science, communicate with data scientists/computer scientists using adequate vocabulary, and foremost formulate research questions that can be addressed with computational methods and/or data extracted from existing web-based data sources.
Course coordinators
Learning outcomes
By the end of the semester students should be able to:
- understand basic concepts of computational social science, such as Natural Language Processing, Computer Simulations, Networks.
- characterize computational methods used in social science.
- understand advantages, challenges, and limitations of computational methods in social sciences.
- formulate research questions that can be addressed with computational methods and/or data extracted from existing web-based data sources.
- plan research using computational methods and tools covered during the class.
Assessment criteria
The final grade will be determined based on the final written project, short tests, and active participation in the discussion.
Active Participation in the discussion (25%)
Before each class with discussion (classes 3, 5, 7, 9, and 11), students will submit the title of the chosen scientific article and a paragraph describing the paper's take-home message. This task could be done individually or collaboratively in groups of two.
Tests (25%)
There will be 5 tests that will check the understanding of the covered concepts. They will be scheduled at the beginning of classes 4, 6, 8, 10, and 12.
Research project proposal (50%)
To pass the course students will write a research project proposal in which they formulate a research problem that can be addressed with the methods discussed during the course as well as explain how this question may be answered (what data should be collected, how it should be processed and analyzed etc.). During the last class, students will present their ideas in the classroom and will have the chance to get early feedback before writing the proposal.
Grades will be assigned according to the following scale:
5 – 90-100% – outstanding performance
4+ – 85-89
4 – 75-84% – good performance
3+ – 70-74
3 – 60-69% – minimum passing performance
2 – 59% or less – performance not suitable for passing
Students are allowed to miss up to 2 classes without any formal excuse (i.e. sick leave). An additional 2 classes can be missed in case of a formal excuse. However, students are encouraged to schedule a meeting with the instructor during office hours if they miss a class.
Additional information
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: