Stylo ver. 0.6.5

[Maciej Eder]

Dear All,

it's been long time since the last update of the package 'stylo'. Time is so limited, it turns out! Hopefully, the very long list of the package's features to be implemented, will be slowly but surely addressed. 

The version 0.6.5 which has been launched today, implements (optionally) an interactive visualisation of the Bootstrap Consensus Networks method via the function stylo.network(). This is the very method that is routinely -- and quite mistakenly! -- referred to as "Gephi Analysis" by several 'Stylo' users. In fact, it has nothing in common with Gephi except that a network visualisation tool (any tool, including Gephi) might be a nice supplement. More on the method can be found here:

Eder, M. (2017). Visualization in stylometry: Cluster analysis using networks. Digital Scholarship in the Humanities, 32(1): 50-64, https://doi.org/10.1093/llc/fqv061

The new implementation involves an interactive visualisation that appears in a web browser, and can be further zoomed and/or manipulated. To make it work, you have to install the networkD3 package. To do so, type:

install.packages("networkD3")

Now, the installation of the newest version of 'Stylo'. In a couple of days, it will be spread across the CRAN mirrors. If you're not patient enough, try more adventurous methods. A convenient way to install R packages directly from the GitHub repository is to use the package devtools. Unless you have already installed it, you should do it by typing:

install.packages("devtools")

Then, install the package stylo:

library(devtools)

install_github("computationalstylistics/stylo")

Alternatively, download the package from here; save the file anywhere on your computer where you will be able to find it; launch R; set working directory to the folder where the downloaded file is:

setwd("i/hope/i/can/remember/where/it/was/")

Install the package:

install.packages("stylo_0.6.5.tar.gz", repos = NULL, type = "source")

Usage is straightforward. Rather than using the function stylo(), try stylo.network() and set the usual input parameters. A minimal quick-start example that is self-contained (the corpus of a dozen American Southern writers be used, as provided by the package 'Stylo') might look as follows. Just copy-paste the following code, and click OK on the GUI:

library(stylo)

data(lee)

stylo.network(frequencies = lee)

Have fun! The Bootstrap Consensus Networks was meant to do Distant-Reading-style analysis of larger corpora. That's probably the good moment to mention the COST action "Distant Reading" (http://www.cost.eu/COST_Actions/ca/CA16204) that has just been launched! You might want to ask Christof for more information, or maybe this is an appropriate forum to provide some essential information in a separate thread of this discussion list?

All the best,

Maciej