1. Mess with Text: textual analysis using AntConc and TagAnt
Liorah Golomb, Humanities Librarian University of Oklahoma ResBaz OU 2017

2. Find text to mess with
Project Gutenberg (public domain, mostly pre-1923)
tvsubtitles.net
Any HTML that can be saved as text using Notepad or any text editor
PDF and Word docs, using a tool such as AntFileConverter
Epubs, Kindle books, etc. using a tool such as Calibre

3. The tools
AntConc
A freeware corpus analysis toolkit for concordancing and text analysis.
TagAnt
A freeware Part-Of-Speech (POS) tagger built on TreeTagger (developed by Helmut Schmid).
Developer: Laurence Anthony, Waseda University
Laurenceanthony.net

4. The corpora
Common Sense by Thomas Paine (1776). Project Gutenberg Ebook #147. The Federalist Papers by Alexander Hamilton, John Jay, and James Madison ( ). Project Gutenberg Etext #1404. The Tweets of Donald J. Trump, Jan. 20-Oct. 3 ,7:30 a.m., Via Trump Twitter Archive.

5. Basic AntConc features
Create word list from one or multiple text files
Use concordance to find specific words
Compare one corpus to another using tool preferences
Find a term in context
Find the words near a term using collocates
Find the words surrounding a term using clusters/n-grams
Create a keyword list by comparing a corpus to a larger standard corpus
Can use truncation (*)
Export results to text file

6. Some comparisons
Thomas Paine used 3817 individual words in Common Sense (word count ~21736) words were used only once. Use of word sad=0, awful=1, bad=4, terrible=0, fake=0
Hamilton et al. used 8608 individual words in the Federalist Papers (word count ~129423) words were used only once. Use of word sad=0, awful=4, bad=14, terrible=0, fake=0
Trump used 4797 individual words in his tweets* (word count ~29935) words were used only once.** Use of word sad=15, awful=0, bad=43, terrible=15, fake=114.
*Stripped of retweets but not of date and time stamps. Also not stripped, URLs or components of URLs.
** Includes strings of letters that were part of a URL.

7. TagAnt part of speech tagger
Creates a new file labelled as tagged and places it in the same folder as the corpus examined
Sort vertically to place into a spreadsheet
Column A=word, Column B=tag, Column C=lemma
Interpret the tags using a site such as the Penn Treebank Project or (my preference) Georgetown’s