Rectangling (Social) Network Data, Advanced Options

Link features, for link prediction

This walkthrough is a follow up on my previous post about rectangling network data As a recap: we want to predict links between nodes in a graph by using features of the vertices. In the previous post I showed how to load flat files into a graph structure with {tidygraph}, how to select positive and negative examples, and I extracted some node features. Because we want to predict if a link between two nodes is probable, we can use the node features, but there is also some other information about the edges in the graph that we cannot get out with node features only procedure. [Read More]

Reading in an epub (ebook) file with the pubcrawl package

In this tutorial I show how to read in a epub file (f.i. from your ebook collection on you computer) into R with the pubcrawl package. In emoji speak: πŸΊπŸ“–πŸ“¦ . I will show the reading in part, (one line of code) and some other actions you might want to perform on textfiles before they are ready for text analysis. After you read in your epub file you can do some cool analyses on it, but that is part of the next blogpost. [Read More]