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

Gurantor department	Department of Computer Science	Credits	3
Subject guarantor	doc. Mgr. Miloš Kudělka, Ph.D.	Subject version guarantor	doc. Mgr. Miloš Kudělka, Ph.D.
Study level	undergraduate or graduate	Requirement	Optional
Year	2	Semester	winter
		Study language	English
Year of introduction	2019/2020	Year of cancellation
Intended for the faculties	FEI	Intended for study types	Bachelor

Instruction secured by
Login	Name	Tuitor	Teacher giving lectures
KUD007	doc. Mgr. Miloš Kudělka, Ph.D.

Extent of instruction for forms of study
Form of study	Way 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

Lectures
Tutorials

Summary

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.

E-learning

Other requirements

Additional requirements are not placed on the student.

Prerequisities

Subject has no prerequisities.

Co-requisities

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 name	Type of task	Max. number of points (act. for subtasks)	Min. number of points	Max. počet pokusů
Credit	Credit	100	51	3

Mandatory attendence participation: Je vyžadována stoprocentní účast na cvičeních s výjimkou nemoci potvrzené od lékaře.

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Conditions for subject completion and attendance at the exercises within ISP: Completion of all mandatory tasks within individually agreed deadlines.

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Occurrence in study plans

Academic year	Programme	Form	Study language	Tut. centre	Year	Type of duty
2024/2025	(B0613A140010) Computer Science	P	English	Ostrava	2	Optional	study plan
2023/2024	(B0613A140010) Computer Science	P	English	Ostrava	2	Optional	study plan
2022/2023	(B0613A140010) Computer Science	P	English	Ostrava	2	Optional	study plan
2021/2022	(B0613A140010) Computer Science	P	English	Ostrava	2	Optional	study plan
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 name	Academic year	Form of study	Study language	Year	W	S	Type of block	Block owner

Assessment of instruction

Předmět neobsahuje žádné hodnocení.