Lecture

quizzes (not obligatory but recommended)
one online test (“midterm”)
- during the practicals
- 1. 1. – 4. 12. (1. 12. or 2. 12.)
homework
practical project
final exam
last lecture = trial exam
- we can pass the exam (but it won't be noted if we don't)
we need to present the project before the exam (→ before Christmas)
https://networksciencebook.com/

Motivation

link analysis
- find relationships among the data
- visualize the links and relationships
applications: telecommunications, criminalistics, marketing
Milgram: six degrees of separation

Scale-Free Networks
- some nodes (= hubs) have extremely many connections to other nodes
- most nodes have just a few connections to other nodes
- resilience to random disturbance
- vulnerability to attacks
- → new application areas (malware protection, medicine, business)
- different than random graphs (normal distribution of the number of edges)
Erdős number
examples: social networks, biological networks, socio-technical networks
mechanisms: growth, preferential attachment
“the rich get richer” (new nodes prefer to attach to nodes that are already popular)
reliability
- random failures: 80 % of randomly selected nodes can fail without framenting the cluster
- coordinated attacks: the elimination of 5–15 % of all the hubs can cause the entire system to collapse