# Graph theory

## Applying Network Science to Reddit: Key Content Detection (Part 2)

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.

## Red Prism - Network Science Applied to Reddit

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

## Applying Network Science to Reddit: Key Content Detection (Part 1)

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.

## Applying Network Science to Reddit: Introduction

Although my research tends to stay in the $C^\infty$ domain, I decided this term to take a course on Networked and Distributed systems. The course takes a dip into applications of dynamical systems on nodes of a graph, which is a marked departure from my usual comfort zone. In this spirit, I decided to take an even farther trip away from my domain of control into the forest of network science for the purpose of my course project.