Network Analysis: Overview and Applications To Population Science

Ceren Budak and Daniel Romero

June 4th, 2019

The PDHP workshop series resumes with our first workshop of the summer: Network Analysis: Overview and Applications To Population Science. Please join instructors Ceren Budak and Daniel Romero (both from U of M School of Information and formerly Microsoft Research) for a half-day workshop geared toward population researchers and data scientists of all experience levels.  The workshop features 2 hours of lecture (covering fundamental principles and theory of network analysis) followed by 2 hours of lab (simulation-based information diffusion within networks and optimal seed node selection), while exploring the connections between network analysis and social research.

Topics include:

• Basic concepts of networks and network data
• Measuring network properties such as centrality and node/edge importance
• Various models of information diffusion and cascade effects
• Network-based classification methods (including Random Walk and K-nearest neighbors)
• Network simulation using Python
• Impact of seed node selection on network properties.

Slides:

Workshop slides are available for download here.

Software:

The lab portion of this workshop is conducted using Python 3 and Jupyter Notebooks, using two Python modules (matplotlib and networkx).  Install links for the software are below:

–Python3 (required)

–Matplotlib (required)

–Networkx (required)

–Jupyter Notebook (strongly recommended, but other Notebooks/IDEs should also work)

If using the pip command, you can install with 4 lines of code:

python -m pip install --upgrade pip
python -m pip install -U matplotlib
python -m pip install -U networkx
python -m pip install -U jupyter