htn: htn: Model and analyze historical text networks

In michaelgavin/htn: Build a historical text network.

Description

The htn package buils on tei2r to perform social-network analysis on bibliographic metadata, derived from the Text Creation Partnership collection.

What it does

The basic purpose of the htn package is to convert bibliographic metadata to networks of co-publication. It comes with a dataset, called tcpEdges, that includes the names of printers, booksellers, and authors that each document is attributed to. It then converts that data into the form of a social-network graph using the igraph package.

The main functionality of the package is to identify networks and then parse those networks into communities, allowing researchers to identify subsets of the EEBO-TCP corpus based on co-publication data. These subsets can then be downloaded, imported into R, and topic modeled using tei2r, or analyzed using empson, which has a variety of functions for text analysis.

For a tutorial that walks through the basics, check out the introductory vignette, "Introduction: Getting Started with htn."

Basic operations:

• buildNetwork: Convert a tei2r::docList into a social network graph.

• communitySubnetwork: Identify subsets of the TCP collection that correspond to different clusters of co-publication.

• drawGraph: Visualize historical text networks.

Sample Data:

• tcpEdges: A dataframe with source-target data over the entire EEBO-TCP Phase I collection.

• tcpPersons: A dataframe with name and role identifiers for each person included in the tcpEdges edge list

Author(s)

Authors: Michael Gavin and Travis Mullen

michaelgavin/htn documentation built on May 22, 2019, 9:50 p.m.