SNA_with_R.Rmd

---
title: "Quick introduction to SNA with R"
author: 
  name: "Raffaele Vacca"
  email: "[raffaelevacca.com](https://www.raffaelevacca.com/)"
  affiliation: "University of Milan"
date: '`r Sys.Date()`'
knit: (function(inputFile, encoding) {
  rmarkdown::render(inputFile, encoding = encoding, output_file="./docs/index.html") })
output: 
  html_document:
    toc: true
    number_sections: true
    toc_float: true
    theme: flatly
---

Quick introduction to [`igraph`](https://igraph.org/r/) and [`ggraph`](https://ggraph.data-imaginist.com/) for SNA in R, materials for my PhD seminars at [Unimi](https://www.nasp.eu/training/phd-programmes/esls.html) and [Unimib](https://en.unimib.it/education/doctoral-research-phd-programmes/phd-programmes/urbeur-%E2%80%93-urban-studies). Download materials [here](https://github.com/raffaelevacca/Intro-SNA-with-R) (GitHub).

```{r include=FALSE}
# Set up root directory to project directory (not Rmd file directory)
# knitr::opts_knit$set(root.dir = '../')
```

```{r include=FALSE, cache=FALSE}
# Read script in
knitr::read_chunk("SNA_with_R.R")
```

# Importing and visualizing network data

* Import network data from external edge list.
* Import node attributes from external dataset.
* Plot networks with `igraph` and with `ggraph`.
* Plot with different network layouts.

```{r import, echo = TRUE, message = FALSE}
```

# Network objects and attributes 

* Vertex and edge attributes.
* Use vertex and edge attributes to analyze network composition.
* Use vertex and edge attributes to analyze network structure.
* Visualize characteristics of network composition and structure.

```{r attr-indexing, echo = TRUE, message = TRUE}
```

# Example of network measures: centrality

* Import network data from external adjacency matrix.
* Calculate and analyze centrality measures.
* Visualize centrality in network plots.

```{r centrality, echo = TRUE, message = TRUE}
```