# Lecture

- quizzes (not obligatory but recommended)
- one online test (“midterm”)
    - during the practicals
    - 30. 11. – 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

### SF-Networks

- 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

## Background

- social science, network analysis, graph theory
- “ego” network
- syphilis outbreak