Slide Set 07: Random Networks, Nutshellfully
A brief reprise of the imagined pure random networks, and their very useful extension to allow for arbitrary degree distributions.
Simple, flat slides:
38M
; Last updated: 2021/02/02, 12:03:13
Printable handout:
8.5M
; Last updated: 2021/02/01, 22:15:55
Slides with all reveals for lectures:
38M
; Last updated: 2021/02/02, 12:03:36
Covered in these episode(s) and clip(s):
Clip 1: Random Networks intro (6:43)
Clip 2: Construction methods 1/2 (6:32)
Clip 3: Visual examples of random networks (7:37)
Clip 4: Phase transition: The appearance of the Giant Component (2:42)
Clip 5: Clustering = 0 for random networks (3:04)
Clip 6: Pure random networks have Poission degree distributions (6:16)
Clip 7: Generalized random networks, or The Configuration Model (6:10)
Clip 8: Construction methods 2/2 (6:23)
Clip 9: Motifs (2:43)
Clip 10: Edge-degree distribution (11:44)
Clip 11: Upsettingly strange friends (4:39)
Clip 12: The giant component condition for random networks (7:23)
Clip 13: A better spreading condition (9:40)
Clip 14: Erdős–Rényi networks: Giant component condition (1:14)
Clip 15: Scale-free networks: Giant component condition (5:02)