Fall 2017

Tuesdays 9:30am-12:20pm

Hawn Conference Room, Hamon Arts Library, SMU, 6100 Hillcrest Ave, Dallas, TX 75205

Text Mining

Prof. Jo Guldi with support from Ben Williams and Katherine Harclerode

Text Mining teaches methods applicable to any field where the meaning of words and phrases must be compared across many instances of speech, adding quantitative measurement to any field where semantic analysis is at the core of an argument. The course presumes no prior knowledge of coding but will rapidly take students up to a point where they can analyze text on their own, based on the most recent innovations in Machine Learning, network analysis, and database design. The techniques discussed here are pertinent to analyzing texts in any discipline where interpretation depends on understanding keywords, whether the texts themselves are legal, political, literary, philosophical, religious, or psychological in nature.

Our textbook begins with word counts in Jane Austen, and by the end of lesson one we'll be comparing Austen's lexicon with Brontë's. Students will quickly proceed to quantifying how particular keywords and key phrases co-occur in the text. By the end of the session, students will know how to teach a computer to statistically identify a "topic" of words that frequently co-occur across many texts. We will visualize word counts as bar graphs, pie charts, frequency plots, and heatmaps, allowing students easily to generalize their findings into presentable evidence.

These skills will place students well on the way to discerning, with quantitative tools, how discourses change over time, and making quantitative claims about the most important terms, authors, or events in a changing discourse.

There are four ways of enrolling in the course:

as an ordinary undergraduate course, with sample exercises throughout and a final project (register for Hist 3380)
as an ordinary graduate course, with a paper applying the methods to texts and arguments in one's home discipline at the end (register for Hist 5392-002)
as a 1-credit course, grad or undergrad, taken over 5 weeks in the middle of the semesterfor the practicum of text mining skills (no reading and discussion, no final project): for this option, please write me directly to be placed on a list; the credit will be filed for retroactively.
as a 5-week practicum, no credit: for faculty, staff and graduate students post-coursework, as space allows (please write to me directly to be placed on a list)

Institutional Goals:

Enable faculty in fields related to semantic analysis of meaning in texts to add text mining methods to their scholarship
Create a cohort of students actively pursuing research through text mining in R
Build up a cohort of librarians who are able to support student and faculty text mining in R
Build up a cohort of IT staff who are able to support student and faculty text mining in R

Individual Goals:

Become comfortable with basic programming in R
Be able to load data, especially texts, into R
Be able to clean and wrangle data, especially texts, in R
Be able to calculate basic text mining statistics from texts, e.g. word counts, sentiments, etc.
Be able to make various plots with these text mining outputs

Vision:

This course is an introduction to basic text mining techniques using the power of computers. The goal is for students to be able to implement text mining on their own texts of interest.
No programming experience is required, and the students will be walked through all aspects of programming for text mining.
The programming language used here is the free and open source software R. There are other programming languages that can be used for text mining, but for now we will focus on R. At the end of this course, students will be able to find a text of their choice, load it into R, and derive knowledge from it using text mining techniques.

Tools:

R
RStudio
Your own laptop, brought to class fully charged each day

Books:

Text Mining with R: A Tidy Approach, by Julia Silge and David Robinson (TMR)
R for Data Science, by Garrett Grolemund and Hadley Wickham (helpful but not required) (R4DS)
The Hitchhikers Guide to ggplot2 in R, by Jodie Burchell and Mauricio Vargas (helpful but not required, it is available for free on leanpub) (HGGPLOT2)

Assessment

Final assignment: 25%

Participation in discussions and workshops: 25%

Quizzes: 25%

Coding assignments: 25%

Assignments

Prepare a handout: What matters in measuring language change over time?

Due Aug 29 at 9:30am

2 points possible.

Handout explaining one digital humanities article

Due Sep 5 at 9:30am

2 points possible.

Installation Screenshots

Due Sep 11 at 11:59pm

1 points possible.

Chapter 1 Graph Submission

Due Sep 15 at 11:59pm

1 points possible.

Chapter 1 Quiz

Due Sep 18 at 11:59pm

4 points possible.

Chapter 2 Graph Submission

Due Sep 22 at 11:59pm

1 points possible.

Chapter 2 Quiz

Due Sep 25 at 11:59pm

4 points possible.

Plotting Assignment

Due Sep 29 at 11:59pm

1 points possible.

Reading Data & Graphing

Due Oct 6 at 11:59pm

1 points possible.

(Grad students only) second final project proposal

Due Oct 8 at 11:59pm

1 points possible.

One page final project proposal

Due Oct 15 at 11:59pm

1 points possible.

Chapter 5 Graph Submission

Due Oct 20 at 11:59pm

No submission for this assignment. 1 points possible.

Chapter 6 Graph Submission

Due Oct 27 at 11:59pm

1 points possible.

Final Project One (Undergrad and grad)

Due Nov 28 at 9am

20 points possible.

Final Project Two (grad students only)

Due Dec 5 at 9am

OFFICE HOURS:

Time: Monday-Thursday 10am-11am

Location: 60 Dallas Hall

Book in advance: http://joguldi.youcanbook.me/

Office hours are when professors make themselves available to students. You may come to discuss the class, your written work, any feedback you've gotten, but also your ideas about the reading, the subject of history more generally, and your ambitions and career. There is no limit to how many times you may come to office hours.

Reservations exist to help students who need particular attention secure a time for a meeting, but Prof. Guldi is almost always in her office during these times and you may also just swing by unscheduled if no one else is booked for the time in question.

Please be courteous enough to cancel any appointments you have made if you are unable to keep the appointment. This will free up the slots for other students.

Course Summary:

Date

Details

Tue Aug 22, 2017

Thu Aug 24, 2017

Tue Aug 29, 2017

Understanding Language	9:30am to 12:20pm
Prepare a handout: What matters in measuring language change over time?	due by 9:30am

Tue Sep 5, 2017

Reading about the revolution in the disciplines	9:30am to 12:20pm
Handout explaining one digital humanities article	due by 9:30am

Mon Sep 11, 2017

Tue Sep 12, 2017

Fri Sep 15, 2017

Mon Sep 18, 2017

Tue Sep 19, 2017

Fri Sep 22, 2017

Mon Sep 25, 2017

Tue Sep 26, 2017

Fri Sep 29, 2017

Tue Oct 3, 2017

Fri Oct 6, 2017

Sun Oct 8, 2017

Tue Oct 10, 2017

Sun Oct 15, 2017

Tue Oct 17, 2017

Fri Oct 20, 2017

Tue Oct 24, 2017

Fri Oct 27, 2017

Tue Oct 31, 2017

Tue Nov 7, 2017

Tue Nov 14, 2017

Tue Nov 21, 2017

Tue Nov 28, 2017

Final Project One (Undergrad and grad)	due by 9am
Final project presentations (undergrad and grad)	9:30am to 12:20pm

Tue Dec 5, 2017

Final Project Two (grad students only)	due by 9am
Final project presentations (grad students only)	9:30am to 12:20pm

COURSE POLICIES:

Meeting attendance.

Attendance at all meetings is required. Failure to attend a meeting for any reason, excused or unexcused, will result in the docking of one unit per missed lecture from the final grade, i.e. from an A- to a B+, which can only be made up by submitting a ten-page paper on the reading in question. Students who have more than two unexcused absences for the class as of Sep. 27 will be automatically dropped.

Late papers.
Papers are expected to be turned in promptly on the deadline. For every day a paper is late past the deadline, beginning the minute after the due date time listed on Canvas, the paper grade will be reduced one graded unit, i.e. from an A- to a B+.

Disability accommodations.

Students needing academic accommodations for a disability must first register with Disability Accommodations & Success Strategies (DASS). Students can call 214-768-1470 or visit http:// www.smu.edu/Provost/ALEC/DASS to begin the process. Once registered, students should then schedule an appointment with the professor as early in the semester as possible, present a DASS Accommodation Letter, and make appropriate arrangements. Please note that accommodations are not retroactive and require advance notice to implement.

Plagiarism, cheating, or sabotage.

The SMU honor code requires that if the professor or another student suspect a student of plagiarism, cheating, or sabotage that the case be submitted to the Honor Council, where it will be evaluated by a panel of faculty and students. Plagiarism will result in automatically failing the course and may result in suspension or explusion from the university. http://www.smu.edu/StudentAffairs/StudentLife/ StudentHandbook/HonorCode

Religious Observance.

Religiously observant students wishing to be absent on holidays that require missing class should notify their professors in writing at the beginning of the semester, and should discuss with them, in advance, acceptable ways of making up any work missed because of the absence. (See University Policy No. 1.9.)

Excused Absences for University Extracurricular Activities.

Students participating in an officially sanctioned, scheduled University extracurricular activity should be given the opportunity to make up class assignments or other graded assignments missed as a result of their participation. It is the responsibility of the student to make arrangements with the instructor prior to any missed scheduled examination or other missed assignment for making up the work. (University Undergraduate Catalogue)

Seeking help in general.

Dedman College policy encourages you to consult with your professor as soon as you notice that attendance, research, or writing are difficult: “If you have a special problem with attendance, confer 5with your instructor. Do not just stop attending your classes. Your teachers will announce their office hours at the beginning of each semester; you can visit their offices during these hours or request an appointment for a conference. If you experience difficulties with any phase of the course, see your teacher immediately. Do not wait until these problems become insurmountable.” There are many, many resources within reach, including this professor. A wise student will consult them, without shame, as soon as s/he notices him/herself having difficulties in this or any course.