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Undergraduates Collaborating in
  Digital Humanities Research
   NITLE Digital Scholarship Seminar
            April 27, 2012
Panelists
• Moderator: Janet Simons, Associate Director of
  Instructional Technology, Co-Director, Digital
  Humanities Initiative (DHi), Hamilton College
• John Burnett, Wheaton College
• Sarah Schultz, Hamilton College
• Amanda Kleintop, University of Richmond
• Gabrielle Kirilloff, University of Pittsburgh
• Janis Chinn, University of Pittsburgh
John Burnett, Wheaton College

• Wheaton College Digital History Project
• http://wheatoncollege.edu/digital-history-
  project/
Sarah Schultz, Hamilton College
• Agha Shahid Ali Poetry Project
• http://asa.dhinitiative.org/demo/index.html
Amanda Kleintop, University of Richmond

• History Honors Thesis, “Networks of
  Resistance: Black Virginians Remember Civil
  War Loyalties”
Undergraduates Collaborating in Digital Humanities Research
Gabrielle Kirilloff, University of Pittsburgh

How Digital Tools Impact Research
 Questions and Methodologies in
         Literary Studies
         http://ft.obdurodon.org
         http://gk.obdurodon.org
Research overview
• Previous research
  – Speech as agency
  – Speech hierarchies
• Research question
  – What are the correlations among speech, gender,
    and moral alignment?
Research methodologies
• Why XML?
  – Unique, descriptive tags
  – Processing a large number of tales
  – Creating multiple views of the same data
• Learning XML and related technologies
The website
The website
The website
The website
The impact of DH
•   Examining a large number of texts
•   The power of visualizations
•   Creating a research tool
•   Looking at texts differently
Studying Register
Variation Using
Computational Methods
Janis Chinn
University of Pittsburgh
April 27, 2012

http://twitter.obdurodon.org/
To what extent do twitter users exercise
register shifting when communicating
with twitter users at large, non-verified
users, and verified users?



              Research Question
Linguistic Register
• Situation-specific variety of language

• Spoken Register
  • Unconscious effort
  • Acquired naturally

• Written Register
  • Conscious effort
  • Acquired through study
Corpus Building
• Python script collects
  tweets from the public        • Current Statistics:
  timeline
• Shell scripting and Perl
  filter down the corpus        •   Total words: 5,375,767
• XML encoded, accessed via     •   Unique words: 654,755
  XQuery                        •   Type-token ratio: 0.12
                                •   Average tweet length (words): 10.36
•   English tweets              •   Average tweet length (characters):
•   US and Canada                   60.39
                                •   Total tweets: 519,018
•   Currently 519,018 tweets
                                •   Total authors: 483,940
•   98% accurate filtering to
    English only text           •   Total verified authors: 687
                                •   Total non-verified authors: 483,253
What’s next?
• Judge tweets on relative register based on:
   • Expletives and profanity
   • Rate of non-dictionary word usage
   • Average word length of dictionary words
   • Appropriate capitalization
   • Standard punctuation
     • Leetspeak
     • Chatspeak
  • Ratio of function words within a tweet

• Potential additions:
  • Analysis of word n-grams and character bi-grams
  • Prescriptive use of ‘whom’ over ‘who’.
• “…The Telegraph quoted an actor and a
  television producer emitting typically
  brainless "Kids Today" plaints about how
  modern modes of
  communication, especially Twitter, are
  degrading the English language, so that
  "the sentence with more than one clause is
  a problem for us", and "words are getting
  shortened".“ –Mark Liberman, Language
  Log, 2011

                 Motivations
• Impossible without DH
• Quantifiable and repeatable results
• Empowering to build and manipulate tools
  to work with data




                 Motivations

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Undergraduates Collaborating in Digital Humanities Research

  • 1. Undergraduates Collaborating in Digital Humanities Research NITLE Digital Scholarship Seminar April 27, 2012
  • 2. Panelists • Moderator: Janet Simons, Associate Director of Instructional Technology, Co-Director, Digital Humanities Initiative (DHi), Hamilton College • John Burnett, Wheaton College • Sarah Schultz, Hamilton College • Amanda Kleintop, University of Richmond • Gabrielle Kirilloff, University of Pittsburgh • Janis Chinn, University of Pittsburgh
  • 3. John Burnett, Wheaton College • Wheaton College Digital History Project • http://wheatoncollege.edu/digital-history- project/
  • 4. Sarah Schultz, Hamilton College • Agha Shahid Ali Poetry Project • http://asa.dhinitiative.org/demo/index.html
  • 5. Amanda Kleintop, University of Richmond • History Honors Thesis, “Networks of Resistance: Black Virginians Remember Civil War Loyalties”
  • 7. Gabrielle Kirilloff, University of Pittsburgh How Digital Tools Impact Research Questions and Methodologies in Literary Studies http://ft.obdurodon.org http://gk.obdurodon.org
  • 8. Research overview • Previous research – Speech as agency – Speech hierarchies • Research question – What are the correlations among speech, gender, and moral alignment?
  • 9. Research methodologies • Why XML? – Unique, descriptive tags – Processing a large number of tales – Creating multiple views of the same data • Learning XML and related technologies
  • 14. The impact of DH • Examining a large number of texts • The power of visualizations • Creating a research tool • Looking at texts differently
  • 15. Studying Register Variation Using Computational Methods Janis Chinn University of Pittsburgh April 27, 2012 http://twitter.obdurodon.org/
  • 16. To what extent do twitter users exercise register shifting when communicating with twitter users at large, non-verified users, and verified users? Research Question
  • 17. Linguistic Register • Situation-specific variety of language • Spoken Register • Unconscious effort • Acquired naturally • Written Register • Conscious effort • Acquired through study
  • 18. Corpus Building • Python script collects tweets from the public • Current Statistics: timeline • Shell scripting and Perl filter down the corpus • Total words: 5,375,767 • XML encoded, accessed via • Unique words: 654,755 XQuery • Type-token ratio: 0.12 • Average tweet length (words): 10.36 • English tweets • Average tweet length (characters): • US and Canada 60.39 • Total tweets: 519,018 • Currently 519,018 tweets • Total authors: 483,940 • 98% accurate filtering to English only text • Total verified authors: 687 • Total non-verified authors: 483,253
  • 19. What’s next? • Judge tweets on relative register based on: • Expletives and profanity • Rate of non-dictionary word usage • Average word length of dictionary words • Appropriate capitalization • Standard punctuation • Leetspeak • Chatspeak • Ratio of function words within a tweet • Potential additions: • Analysis of word n-grams and character bi-grams • Prescriptive use of ‘whom’ over ‘who’.
  • 20. • “…The Telegraph quoted an actor and a television producer emitting typically brainless "Kids Today" plaints about how modern modes of communication, especially Twitter, are degrading the English language, so that "the sentence with more than one clause is a problem for us", and "words are getting shortened".“ –Mark Liberman, Language Log, 2011 Motivations
  • 21. • Impossible without DH • Quantifiable and repeatable results • Empowering to build and manipulate tools to work with data Motivations