460-2067/02 – Introduction to Social Network Analysis (UASS)

Gurantor departmentDepartment of Computer ScienceCredits3
Subject guarantordoc. Mgr. Miloš Kudělka, Ph.D.Subject version guarantordoc. Mgr. Miloš Kudělka, Ph.D.
Study levelundergraduate or graduateRequirementOptional
Study languageEnglish
Year of introduction2019/2020Year of cancellation
Intended for the facultiesFEIIntended for study typesBachelor
Instruction secured by
LoginNameTuitorTeacher giving lectures
KUD007 doc. Mgr. Miloš Kudělka, Ph.D.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Credit 1+2

Subject aims expressed by acquired skills and competences

200/5000 Upon completion of this course, students will be able to describe the essentials of basic problems related to the analysis of social networks; they will be able to use selected APIs and tools for analysis and visualization of small networks.

Teaching methods



The subject aims to provide basic information about the history and present of social networks and foundations of their analysis.

Compulsory literature:

Barabási, A. L. (2014). Network science book. Boston, MA: Center for Complex Network, Northeastern University. Available online at: http://barabasi. com/networksciencebook.

Recommended literature:

Barabási, A. L. (2016). Network science. Cambridge university press.

Way of continuous check of knowledge in the course of semester

Solving tasks assigned to the exercises.


Other requirements

Additional requirements are not placed on the student.


Subject has no prerequisities.


Subject has no co-requisities.

Subject syllabus:

Lectures History and present of social networks. Basic features of social networks. Simple measurement of social network features and their purpose. Ego-networks analysis Selected social network APIs (Facebook, Twitter,...). Tools for social network analysis. Tools for social network visualization. Interpretation of social network analysis results Seminars The exercises will be devoted to practical tasks in the following areas: - Analysis of features - Practical usage of selected APIs - Network visualization - Interpretation of analytical results

Conditions for subject completion

Full-time form (validity from: 2019/2020 Winter semester)
Task nameType of taskMax. number of points
(act. for subtasks)
Min. number of points
Credit Credit 100  51
Mandatory attendence parzicipation: Je vyžadována stoprocentní účast na cvičeních s výjimkou nemoci potvrzené od lékaře.

Show history

Occurrence in study plans

Academic yearProgrammeField of studySpec.ZaměřeníFormStudy language Tut. centreYearWSType of duty
2020/2021 (B0613A140010) Computer Science P English Ostrava 2 Optional study plan
2019/2020 (B0613A140010) Computer Science P English Ostrava 2 Optional study plan

Occurrence in special blocks

Block nameAcademic yearForm of studyStudy language YearWSType of blockBlock owner