CreateBimodalNetwork: Note: this function is DEPRECATED and will be removed in a...
In SocialMediaLab: Tools for Collecting Social Media Data and Generating Networks for Analysis

Description Usage Arguments Details Value Note Author(s) See Also Examples

Create bimodal networks from social media data

1	CreateBimodalNetwork(x, writeToFile, removeTermsOrHashtags)

`x`	a data frame of class `dataSource`. For Twitter data, it is also possible to provide a list of data frames (i.e. data frames that inherit class `dataSource` and `twitter`). Only lists of Twitter data frames are supported at this time. If a list of data frames is provided, then the function binds these row-wise and computes over the entire data set.
`writeToFile`	logical. If `TRUE` then the network is saved to file in current working directory (GRAPHML format), with filename denoting the current date/time and the type of network.
`removeTermsOrHashtags`	character vector. Default is none. Otherwise this argument specifies which terms or hashtags (i.e. vertices with matching 'name') should be removed from the bimodal network. This is useful to remove the search term or hashtag that was used to collect the data (i.e. remove the corresponding vertex in the graph). For example, a value of "#auspol" means that if there is a vertex with the exact name "#auspol" then this vertex will be removed.

This function creates a bimodal network from social media data (i.e. from data frames of class dataSource, or for Twitter data it is also possible to provide a *list* of data frames), with edges representing relationships between actors of two different types (e.g. Facebook users and Facebook posts, with edges representing whether a user has commented or 'liked' a post).

This function creates a (directed and weighted) bimodal network from a data frame of class dataSource (which are created using the 'CollectData' family of functions in the SocialMediaLab package), or a *list* of Twitter data frames collected using CollectDataTwitter function.

The resulting network is an igraph graph object. This graph object is bimodal because edges represent relationships between vertices of two different types. For example, in a bimodal Facebook network, vertices represent Facebook users or Facebook posts, and edges represent whether a user has commented or 'liked' a post. Edges are directed and weighted (e.g. if user i has commented n times on post j, then the weight of this directed edge equals n).

An igraph graph object, with weighted and directed edges.

Not all data sources in SocialMediaLab can be used for creating bimodal networks.

Currently supported data sources are:

- Facebook - Twitter

Other data sources (e.g. YouTube) will be implemented in the future. Additionally, the user is notified if they try to create bimodal networks for incompatible data sources.

For Twitter data, bimodal networks can be created from multiple data frames (i.e. datasets collected individually using CollectDataTwitter). Simply create a list of the data frames that you wish to create a network from. For example, myList <- list(myTwitterData1, myTwitterData2, myTwitterData3).

Timothy Graham <timothy.graham3@uq.net.au> & Robert Ackland <robert.ackland@anu.edu.au>

See CollectDataFacebook and CollectDataTwitter to collect data for creating bimodal networks in SocialMediaLab.

## Not run: 
  ## This example shows how to collect Facebook page data and create a bimodal network

  # Use your own values for myAppID and myAppSecret
  myAppID <- "123456789098765"
  myAppSecret <- "abc123abc123abc123abc123abc123ab"

  # Authenticate with the Facebook API using `AuthenticateWithFacebookAPI`
  fb_oauth <- AuthenticateWithFacebookAPI(appID=myAppID, appSecret=myAppSecret,
    extended_permissions=FALSE, useCachedToken=TRUE)

  # Run the `CollectDataFacebook` function and store the results in variable `myFacebookData`
  myFacebookData <- CollectDataFacebook(pageName="StarWars", rangeFrom="2014-05-15",
  rangeTo="2014-06-03",writeToFile=FALSE,verbose=TRUE)

  # Create a 'bimodal' network using \code{CreateBimodalNetwork}
  g_bimodal_facebook <- CreateBimodalNetwork(myFacebookData)

  # View descriptive information about the bimodal network
  g_bimodal_facebook

## End(Not run)