Course Description 

The course introduces students to (meta)theoretical assumptions and methodological apparatus of social network analysis (SNA). Each class consists of a lecture that introduces theoretical background and “mechanics” of a given concept or method, and a workshop where students use this knowledge through practical tasks.

The classes 1A/B, 2A/B, and 3A/B introduce software used for data analysis and graphics, which is an open-source freeware R (https://cran.r-project.org/) and R Studio (https://www.rstudio.com/). Students will be familiarized with basic data formats, functions, and data manipulation techniques utilized later in the course. The core of the course then focuses on basic concepts such as connectedness, centrality, or cohesiveness. The last part of the course presents exploratory as well as inferential approaches to network data analysis. Students are obliged to submit assignments as specified further.

Upon successful completion of the course, students will be able to set up an SNA-defined research design, specify appropriate techniques, and rigorously use them. The emphasis will be put on the practical use of this knowledge.

Course Requirements

Attendance is not compulsory but strongly advised. 

The course will be held in person or in a hybrid regime unless the change in epidemiological regulation prohibits it. 

Students are expected to read the required readings for each class. Required readings for the course are to be found either in electronic sources (databases or direct links), the Faculty library, or in the Study Materials folder in Information System.

The students will submit 5 assignments in total as specified in the course schedule. The specific instructions for the assignments are added as comments in the assignment scrips. The assignments are to be submitted via Information System to Homework Vaults in Study Materials within 6 days after the class (Tuesday included). Each of the assignments will be graded between 0 and 10 points. Thus, students can obtain up to 50 points.

Grading

The final grade will be calculated as a sum of the assignments. The maximum is 50 points; the minimum to complete the course is 30 points.

A                                        44 – 50 points

B                                        41 – 43 points

C                                        38 – 40 points 

D                                        34 – 37 points

E                                        30 – 33 points

F                                        less than 30 points

Cheating and plagiarism

Cheating on a written exam or in any other part or aspect of the course will result in the reduction of the final grade to an F. Plagiarism is the use of material written by another person without referencing the source. Plagiary will receive no points and the final grade will be an F. The Disciplinary Commission will be notified about any cases of plagiarism.

In case of uncertainty about how to avoid plagiarism, please follow the instructions mentioned on this link. In case you still have questions, please consult Petr Ocelík via email.