Amice13

read.gspreadsheet <- function(key) {
  require(RCurl)
  myCsv <- getURL(paste("https://docs.google.com/spreadsheet/pub?hl=en_US&hl=en_US&key=", 
                        key, "&single=true&gid=0&output=csv", sep = ""),
                  .encoding = "UTF8")
  read.table(textConnection(myCsv), header = T, sep = ",", stringsAsFactors = FALSE)
}

Amice13

The range sliders at the top change the values for the force-directed algorithm and the buttons load new graphs and apply various techniques. This will hopefully serve as a tool for teaching network analysis and visualization principles during my Gephi courses and general Networks in the Humanities presentations.

Notice this includes a pretty straightforward way to load CSV node and edge lists as exported from Gephi.

It also includes a pathfinding algorithm built for the standard data structure of force-directed networks in D3. This requires the addition of .id attributes for the nodes, however.

Now with Clustering Coefficients!

Also, it loads images for nodes but the images are not in the gist. The code also refers to different network types but the data files on Gist only refer to the transportation network.

Amice13

var open = window.XMLHttpRequest.prototype.open,
    send = window.XMLHttpRequest.prototype.send,
    onReadyStateChange;

function openReplacement(method, url, async, user, password) {
    var syncMode = async !== false ? 'async' : 'sync';
    console.warn(
        'Preparing ' +
        syncMode +
        ' HTTP request : ' +

Amice13

#' Convert the output of a topicmodels Latent Dirichlet Allocation to JSON
#' for use with LDAvis
#'
#' @param fitted Output from a topicmodels \code{LDA} model.
#' @param corpus Corpus object used to create the document term
#' matrix for the \code{LDA} model. This should have been create with
#' the tm package's \code{Corpus} function.
#' @param doc_term The document term matrix used in the \code{LDA}
#' model. This should have been created with the tm package's 
#' \code{DocumentTermMatrix} function.