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Finally we can jump into the analysis! The purpose of this post is to describe the essential model used for detect key content generators or posts and show what happens when we apply the techniques discussed in the previous post to the /r/uwaterloo subreddit. The Model I could dive straight into the model construction, but I think it is of much greater value to spend some time walking through my thought process.

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My first investigation involves attempting to detect key content or users in a given community. I begin by establishing the model and various mathematical preliminaries. Mathematical Preliminaries Basic Definitions Networks can be modelled by nodes that are connected together by edges. The mathematics of Algebraic Graph Theory gives us the tools we need for this section. In this case, we introduce the language used for directed graphs. Definition A graph $G = (V, E)$ is a pair consisting of a set of nodes $V$ and a set of edges $E$ that describe which nodes lead to which others.

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Selected Publications

Provides a set of conditions, in the algebra of differential forms, that can be used to test whether a smooth manifold can be transversely feedback linearized — in a local sense — under a given affine control system.
IEEE CDC, 2018

Projects

Red Prism - Network Science Applied to Reddit

Course project applying the tools of network science to the social network graph of Reddit.

SE499 Independent Research Project

Investigating the performance difference between two different path following control techniques.

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