Text Analysis Without Programming

Lynn Cherny

Visiting Knight Chair

School of Comm, U of Miami

@arnicas / lynn@cherny.com

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Caveat: A talk at the intersection of data vis, journalism, and digital humanities

(Also: Focus here is on free or very cheap tools)

What is text data?

  • Unstructured text write-ins on surveys
  • PDF Documents
  • Books (free or not)
  • Articles (magazine, news, blog...)
  • Comments on articles
  • Tweets, Facebook posts
  • Reviews (books, restaurants)
  • Prisoners' last words on Death Row
  • TV show closed captions
  • Debate or speech transcripts
  • Bills in Congress
  • Email archives
  • Recipes
  • Student essays...

Some Levels of Analysis

  • Word level: What words are used?
  • Word in context: Where are words used?
  • N-grams or phrases: What combinations of words are used?
  • Structure of the text:
    • Sentence length
    • Genre attributes
  • Relationships between texts
    • Similarity/difference
    • Metadata -- citation networks
  • Historical trends in corpora

PDFs are a sad text data reality

Data.gov

PDF to Text

Some Document Corpus Tools Will Take and Convert PDFs for you

But beware... a lot of tools only take text, so you have to do the work first.

Handling Hillary Clinton Emails on a Mac...

  1. Footer on WSJ site: "Download zip files of each document release: May (Benghazi committee)JuneJulyAugust and September."
  2. I got September.
  3. Install xpdf from this site
  4. At bash prompt: 'for f in *.pdf; do pdftotext $f; done'
  5. Move .txt files (and .pdf) into their own directories.

Other data sets I'll use today...

  • Transcripts of the most recent Democratic Candidate and Republican candidate debates (scraped from WaPo)
  • Last statements from prisoners executed in Texas

Simple Word Counts

WSJ (Oct 14)

Using "grep" and "wc"

> grep CLINTON dem_debate_2015_10_13_wapo.txt 

CLINTON: Well, thank you, and thanks to everyone for hosting this first of the Democratic debates.

CLINTON: Well, actually, I have been very consistent. Over the course of my entire life, I have always fought for the same values and principles, but, like most human beings -- including those of us who run for office -- I do absorb new information. I do look at what's happening in the world.

CLINTON: No. I think that, like most people that I know, I have a range of views, but they are rooted in my values and my experience. And I don't take a back seat to anyone when it comes to progressive experience and progressive commitment.

CLINTON: I'm a progressive. But I'm a progressive who likes to get things done. And I know...

.... many more lines....

 

>grep CLINTON dem_debate_2015_10_13_wapo.txt | wc -l

      74

>grep SANDERS dem_debate_2015_10_13_wapo.txt | wc -l

      70

>grep WEBB dem_debate_2015_10_13_wapo.txt | wc -l

      35

Command line!

> wc -w dem_debate_2015_10_13_wapo.txt 

22953 dem_debate_2015_10_13_wapo.tx

> wc -w gop_debate_2015_9_16_wapo.txt 

35127 gop_debate_2015_9_16_wapo.txt

wc is unix for "word count."  wc -w is just count words.  You can also wc -l (lines).

Word Counts in Context :)

On Hillary's emails

>wc -w * | sort 

.... lots of them go by...

1800 C05781926.txt  
1897 C05782687.txt  
2202 C05785187.txt  
2562 C05782645.txt  
2705 C05782303.txt  
3879 C05782890.txt  
4266 C05782607.txt  
4322 C05782571.txt
5697 C05781825.txt
211567 total

Screenshot of shame - trying to change file format on a Mac with regex...

I'm not going to go through this with you, sometimes programming is easier.

Concordance Tools

E.g., AntConc suite (free, all platforms)

Concordances and Basic Corpus Concepts

  • word counts (how many times each word appears)
  • keyword in context (KWIC)
  • collocations (words occurring with a term)
  • n-grams (sequences of N words)
  • stop words (words that are common and may be filtered out from analysis)
  • sometimes, parts of speech (noun, verb, etc)

Keyword in Context Views

Plots

Using AntConc, at what points in the transcripts of the last GOP candidate debate and Democratic candidate debate did "(APPLAUSE)" occur?

transcript source scraped off Washington Post, using AntConc

Look familiar?

N-Grams, or word groups that occur together

Collocates for word "gun"

AntConc on debate transcripts

Network Collocations in Overview Project

Overview Project on sample of Clinton emails

Context of the N-Grams

Word Trees

Formerly in the free Many Eyes, now requires code in Google Charts

Web-Based: Voyant

Web Based: Lexos is Great.

 

Lexos link (does a lot more too)

see also Word Counter

Edging into Stylistics / Genre....

Word Clouds

Wordle site -- uses Java applet, only runs in Firefox/Safari for me

A few Issues with Word Clouds

But geez do people love them.

Without trimming words

 Trimming words

Without trimming words

Trimming words

Lexos site, 

after a lot of stop wording

Turns out...

There are more terms used in GOP debate, but term frequency avg is much higher; more repetition of refrains?

An interesting alternate layout (from a previous debate year)

Incomprehensible

Experimental Relationship

Cool: Word Counting in SOTU Speeches

Machine Learning Applications to Text

  • Sentiment Analysis
  • Entity Extraction
  • Topic Modeling
  • Structural relationships across texts
  • ... more, that usually involve code

Google Sheets Add-in:

Sentiment Analysis

Not sure I buy the sentiment results.

Manual Demos

Entity Recognition

Simple example in Overview Project

Entity Detection in Texas Death Row Last Statements

Who is IRENE??

Overview Project

Document Cloud

a journalistic open source project for document annotation, entity identification, sharing...

Document Cloud Views:

Entities, Timelines

(of course the Hillary emails are in Document Cloud too)

Topic Modeling

Overview Project, on sample of Clinton emails

Topic Modeling Over Time

(an example that was done with code)

NZZ 2014: topics in a year of articles

NZZ site, also done with code

Topic Modeling Tool

Clustering Documents

A small sample of Hillary's emails in Lexos....

?

C05781825.txt

Hierarchical Clustering

Stylometrics (needs R code)

Using Large Public Corpora

Google N-Grams

Google Trends

Historical Document Corpora

Wikipedia

 

WaPo Trends Pieces

WaPo wonkblog, Chris Ingraham

WaPo wonkblog, Emily Badger

N-Grams in Early English

Site (thanks to Heather Froehlich)

Bookworm: Search Bills

Culturomics, Ben Schmidt

Wikipedia Edits

Academic Citation Analysis

You can do a lot without code, but it's often easier to do some simple programming (or use someone's tool/library).

Coding talk coming up...

A Few Sources of Text Data Online

Some Tools Reference Sites

Text Analysis Without Programming

By Lynn Cherny

Text Analysis Without Programming

An intro talk on text analysis relevant to journalists, digital humanists, and anyone with words to analyze. Focused on free or cheap tools, with a lot of visualization, too.

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