Using Simpson's Paradox to Discover Interesting Patterns in Behavioral Data

1 code implementation • 8 May 2018 • Nazanin Alipourfard, Peter G. Fennell, Kristina Lerman

We describe a data-driven discovery method that leverages Simpson's paradox to uncover interesting patterns in behavioral data.

Can you Trust the Trend: Discovering Simpson's Paradoxes in Social Data

2 code implementations • 13 Jan 2018 • Nazanin Alipourfard, Peter G. Fennell, Kristina Lerman

We present a statistical method to automatically identify Simpson's paradox in data by comparing statistical trends in the aggregate data to those in the disaggregated subgroups.

Computers and Society

Multistate dynamical processes on networks: Analysis through degree-based approximation frameworks

2 code implementations • 26 Sep 2017 • Peter G. Fennell, James P. Gleeson

Multistate dynamical processes on networks, where nodes can occupy one of a multitude of discrete states, are gaining widespread use because of their ability to recreate realistic, complex behaviour that cannot be adequately captured by simpler binary-state models.

Physics and Society Dynamical Systems 60J27, 37N25, 05C82, 34B45