slides are available online

• html notes: ericmjl.github.io/big-data-boston-2016
• slides: ericmjl.github.io/big-data-boston-2016/slides.html
• source: github.com/ericmjl/big-data-boston-2016

about myself

• doctoral candidate, MIT biological engineering
• self-taught pythonista
• using networks to solve problems in infectious disease ecology, evolution & biochemistry

outline

1. what are networks?
2. example 1: recommendation systems
3. example 2: panama papers
4. example 3: influenza ecology & evolution
5. example 4: neural networks on networks

what are networks

networks, a.k.a. graphs, are composed of nodes (circles) and edges (lines)

example 1: recommendation systems

if A is connected to B and C, but B and C are not connected, then maybe they should be!

example 1: recommendation systems

if A and B share overlapping interests, then maybe some of B's interests can be recommended to A.¹

example 2: panama papers

graph databases were used to show how the rich hide their money.²

example 3: influenza ecology and evolution

for influenza, gene shuffling probably helps in host switching.³

example 4: neural networks on networks

graph convolutions let us do machine learning on graph-structured data.⁴

visualize networks rationally

move away from the hairball!

visualize networks rationally

rational network visualizations prioritize placement of nodes

conclusions

• think relationally
• networks can be used creatively to solve all sorts of problems

keep in touch

• personal website: ericmjl.com
• linkedin: linkedin.com/in/ericmjl
• datacamp: network analysis course coming within the next few months!
• available for training your staff on data analysis and network science