1. Lab exploration: Network Profile Summary

2. Why? Best way to learn is to experiment rather than to observe.
Transition from knowledge exposure to practice (without mimicking the instructor).
You can experiment on your network:
exploring the topics as we present them, and
as your intellectual curiosity inspires you.

3. How? Choose a network that interests you.
You will be analyzing this network and present results about it.
You are welcome to download a data set from html or other data of interest

4. What?
At the end of each day, create one (or two slides if absolutely needed) with your analysis of the topics presented that day, applied to your network.
Students will present their findings, followed by a group discussion of all the networks’ analysis (similarities and dissimilarities).
The cumulative PPT slides to be presented on Fri, October 26th
Thu, October 25th is lab day, with no new lecturing .
Your presentation should be convincing, coherent, and cohesive.
Let’s see some examples!

5. Terror network 2016 (Ee Hong Aw)
Purpose of this study: examine relationships between terrorist groups based on location of the incident.
Dramatic increase in activities since 2011
142 different countries have been targeted since 2011:
Iraq: 15,620 incidents
Pakistan: 9,125 incidents
Afghanistan: 8,693 incidents
USA: 175 incidents
1Global Terrorism Database:

6. Multiplex Terrorist Nets (Ryan Miller)

7. Multiplex Terrorist Nets (Ryan Miller)
V = 133
E = 2451
Layers = 14
AVG Path Length: 2.13
Clustering Coeff: 0.71
Description: Small, Dark, Real, Multiplex Network of the five Terrorist Organizations in Indonesia rendered as a Monoplex Network by Gephi.
AVG Degree: 23
AVG Weighted Degree: 37 7

8. West Coast Power Grid (Ben McCaleb)
Vertices: N = 4,947
Edges: E = 6,594
Undirected
Non-Weighted
Network Statistics
Avg. Degree: 2.669
Avg. Path Length:
Network Diameter 46
Graph Density 0.001
Modularity
Avg. Clustering Coeff: 0.107
Eignevector Centrality: 0.647

9. Star Wars IV, V, AND VI (Zac Lukens)
Node: characters
Edges based on “interaction”
Talked to
Fought against/with
Related to
Worked for
Bartender
Star wars picture source:

10. HDD mapping (LT Greg Allen)
Automate extraction and construction of the social network of the user(s) of computers: HDD are scanned with forensic bulk extractor for addresses

11. HDD mapping (LT Greg Allen)
Component 4:
Pearson Similarity:
.837
avg degree: 7.678
avg path:
Possibly the address book

12. Email mapping (Miguel Miranda López)
traffic from August ‘15 –Jan ‘16, (received and sent s).
Node: user accounts
Edge: header field users (To, From, CC, BCC)
Colors based on degree
No weights on edges
content mapping
Node: key words
Edges: key words in the same

13. Email mapping (Miguel Miranda López)
k-Core (k=78) Nodes: 40 of 499 (8.0%)
Edges: 1560 of (11.9%) 13

14. NPS Network Science Graduates Network (Erik Kiser)
2014
The Naval Postgraduate School (NPS) offers a Network Science Certificate which has graduate five classes and 54 students since 2014.
Students enrolling in the Network Science Certificate come to NPS from a variety of countries and military organizations. Upon graduation, the students return to their home country and branch of service.
Students in the same Network Science Certificate cohort take at least two classes with one another (MA4027 and MA4404). Temporal separation of the students results in a complete graph for each of the different year groups.
The purpose of this study is to examine if edges exist between students of different Network Science Certificate cohorts based on combined/joint military assignments or a shared course of study at NPS. This study also seeks to analyze information regarding the strength of the various relationships that exist amongst the students.
Nodes represent students who have/are participating in the Network Science program. An edge exists between two students if a relationship exists and the weight of the edge (1-4) represents the strength of the relationship.
2016
2018
2015
2017
Graph derived from partial data a/o 25JAN18
Node colors indicate branch of service (Army, Navy, Marines, Coast Guard, Air Force)
Cohort information overlaid for reference
4 of 54 students responded
Partial data exhibited high modularity and clustering coefficients

15. Community Detection and Node Coloring (Erik Kiser)
NPS Curriculum
Detected Communities
Network Science Cohort
Network a/o 30JAN18
Gephi algorithm repeatedly detected the same communities
Detected communities generally corresponded to Network Science cohorts
13 of 54 students responded
Sorted using Fruchterman Reingold algorithm

16. Network Profile Summary
Network Profile Summary (NPS):
deck of slides on the personal network.
NPS allows students to:
continually apply newly learned concepts to their selected networks  realize the utility and place of these concepts,
find the why behind the what they observed,
be motivated,
be independent learner,
see coursework, concepts, and feedback as productive and globally meaningful rather than corrective and locally meaningful,
engage with topics that mean something to them,
while students are exposed to required material.

17. Thank you!
Ralucca’s
Course info:
Online free textbooks:
Newman's SIAM article (extended to a paid book),
Estrada's article (extended to Estrada's paid textbook),
Easley and Kleinberg's free book, and
Barabasi's free books.