English 391AH (Honors College seminar)
5 September 2019
Introduction to course and books:
- Nick Montfort, Exploratory Programming for the Arts & Humanities. MIT Press. 2016. Amazon.
- Jodie Archer & Matthew Jockers, The Bestseller Code. St. Martins, 2016. (Amazon)
- Bird, Klein, Loper. The Natural Language Tool Kit (free)
- Tim Hall et al., Python 3 for Absolute Beginners (free here)
- Sarah Boslaugh, Statistics in a Nutshell. (Free here)
- Jurafsky & Martin, Speech and Language Processing (free here)
12 September 2019
READ:
- Nick Montfort, Exploratory Programming. Introduction and Installation and Setup, pages 1–26.
Montfort's Introduction is a bit tendentious, but you can ignore that. Ensure that you have a text editor and a Python environment (iPython Notebook or PyCharm or Anaconda). The easiest is Anaconda.
If you can't get it going yet, then you can use python online at tutorialspoint.
An overview on how computers work: this handout.
19 September 2019
READ:
- Nick Montfort, Exploratory Programming. Chapter 1 and Chapter 2, pp. 27–44.
- Explore w3schools and its basic HTML course. What is an HTML page? How is it structured?
- Browse the Preface and Chapter 1 of Statistics in a Nutshell. (Free here). What is data? What are its kinds? Also good is Khan Academy on statistics (linked on the right, below the calendar).
We will discuss HTML and text data. Structuring and cleaning your data is an essential first step. Consider the various methods you have mastered in order to read and analyze literature, history, math, chemistry, and road signs. How might one use these methods to produce structured data?
26 September 2019
READ:
- Nick Montfort, Exploratory Programming. Chapter 3 and Chapter 4, pp. 45–78.
- Remember, you can proctice python online at tutorialspoint. Here is an introductory textbook on python. Extremely good are the vieos from Corey Shaffer and Socratica, found on the right-hand side of the page under "LINKS"
We will look at variables and functions, conditionals, and iteration.
3 October 2019
READ:
- Nick Montfort, Exploratory Programming. Chapter 5 and Chapter 6. Don't spend much time on 5 unless you need to brush up on python.
- Windows Users: here are directions for using the command line.
- Windows Users: how to install and use python. You don't need Visual Studio, but if you want to use it, here is Corey Shaffer on how to install and set up VS.
How is text structured into data? What is a letter, and how does it relate to a sound? What is a word? What is a string and how does it relate to phrases and sentences?
10 October 2019
READ:
What methods do humans use to process and understand texts? if you're looking in a text for information, what precisely are you looking for?
17 October 2019
READ:
How does one research relationships between literary works, whether by the same author or different authors? What kinds of comparisons does one make, and what are the assumptions behind those comparisons? Consider our systematic errors in judgment as described by Tversky and Kahneman.
24 October 2019
READ:
- Archer & Jockers, Bestseller Code. Chapters 1, 2, and 3, pp. 1–111.
- Here are the bestsellers this week: Publishers Weekly
What can we measure in books of fiction and what do we learn? What surprised you about best-selling fiction? How does it differ from what is commonly considered literature?
31 October 2019
READ:
- Archer & Jockers, Bestseller Code. Chapters 3, 4, 5, and 6, pp. 113–242.
What is literary style? Why does it matter?
7 November 2019
PRACTICUM:
- Read Nick Montfort, Exploratory Programming. Chapter 10
- Bring your laptops.
Let's see what we can discover together about some texts from the NLTK corpus.
14 November 2019
PRACTICUM:
- Download a text, clean it, load it into NLTK, tokenize it, and analyze it.
We will vote on which text or group of texts to use. Let's see if we can analyze prose and poetry together, and ask about the different methods required.
21 November 2019
PRACTICUM:
- Download a website (news, magazine, or something like it), use Beautiful Soup to analyze it.
- Some data sets to peruse (via Northeastern U)
- Also briefly, data visualization. Browse Edward Tufte.
- Here is Inge Druckrey on designing typeface.
We will explore non-literary texts.
5 December 2019
WRAP-UP:
What did you learn? What can you do with it? |
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LINKS.
Academic Schedule
Sites
Python.org
Python Packages.
Data Science in general
UMass Library
NLTK
NLTK Book
Topic Modelling (LDA)
Videos
VIDEO: Corey Shaffer Python
VIDEO: Socratica: Python
VIDEO: Khan Academy Statistics
Corpora
Oxford Text Archive
Project Gutenberg
Corpus of Western Lit
Kaggle Data Sets
US Government data
Mass Data sets
MA Attourney General Data
Boston Data
National Weather and more
US Census
UMass Amherst Data
Amherst MA Data
Books & Publishing Data
A million headlines (AUS)
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