Be like me - looping through shortest distance analysis

Introduction I’ve been doing some work lately on social networks that exist between organisations or institutions. This is nice as it builds on some of my dissertation work, and I generally find it quite interesting. Networks that form between organisations are often quite powerful, in that they can illustrate where strong areas of like-minded work exist or where new connections might be useful in strengthing one organisation’s influence. Why like me?

Networks from survey data: Creating mock data

Why create a new dataset? I’d like to do a series of posts looking at social network analysis using primary data (i.e. data collected by yourself.). There are a lot of different examples of when you might want to use a survey to collect data for use in analysing social networks. But that’s for another time. The purpose of this post is to create a new dataset that can be used in practising social network analysis in future posts.

Apples for apples I

Introduction This is the initial Deltanomics blog post. So, in this post, I’ll cover a few different approaches to analysis and data visualisation rather quickly that provides a good overview of the types of things covered in this blog. Let’s start with loading the packages we’ll use. Also, let’s create a ggplot theme that allows us to easily make changes when we want. ## Libraries used in analysis library(tidyverse) library(magrittr) library(scales) library(RColorBrewer) library(janitor) library(ggraph) library(tidygraph) library(graphlayouts) library(flextable) ## a congruent theme throughout for plots post_theme <- function(.