Module Handbook

  • Dynamischer Default-Fachbereich geändert auf INF

Course INF-57-21-K-4

Complex Network Analysis (2V+1U, 4.0 LP)

Course Type

SWS Type Course Form CP (Effort) Presence-Time / Self-Study
- K Lecture with exercise classes (V/U) 4.0 CP 78 h
2 V Lecture 28 h
1 U Exercise class (in small groups) 14 h
(2V+1U) 4.0 CP 42 h 78 h

Basedata

SWS 2V+1U
CP, Effort 4.0 CP = 120 h
Position of the semester 1 Sem. in WiSe
Level [4] Bachelor (Specialization)
Language [DE/EN] German or English as required
Lecturers
Area of study [INF-SI] Socioinformatics
Livecycle-State [NORM] Active

Possible Study achievement

  • Verification of study performance: proof of successful participation in the exercise classes (ungraded)
  • Details of the examination (type, duration, criteria) will be announced at the beginning of the course.

Contents

  • Introduction: small-worlds, network motifs, graph mining, and the Königsberger bridge problem.
  • Graph theoretical definitions Network models and random graphs
  • Project design in network analysis
  • Centrality measures
  • Clustering algorithms I + II
  • Algorithms for network motifs
  • One-mode projections of bipartite graphs
  • Machine learning in network analysis

Literature

  • U. Brandes, T. Erlebach: Network analysis – methodological foundations, Springer Verlag, 2005.
  • D. Easley and J. Kleinberg: Networks, Crowds, and Markets, Cambridge University Press, 2010.
  • Katharina A. Zweig: Network Analysis Literacy, Springer Verlag, Wien, 2016

References to Course [INF-57-21-K-4]

Module Name Context
[INF-90-02-M-4] Modelling of Socioinformatics Systems P: Obligatory 2V+1U, 4.0 LP
Course-Pool Name
[INF-Alg_V-KPOOL-6] Lectures of the teaching area Algorithmics and Deduction