For Thursday (11/16)

For Thursday, we’ll meet in the computer lab (HUM 401).  Let’s make sure all your Wikipedia pages are good to go.  Do you have at least two forms of feedback?  Have you revised your page draft to respond to feedback? Is your prose clear, direct, and error-free?  Are your page formatting and style correct? Our Wikiedu dashboard also suggests some other final considerations.

And, don’t forget to check out our “How to Not Read” assignment – – due November 30.  Bring any questions to class.

For Tuesday (11/14)

For Tuesday, let’s continue our discussion of “collective intelligence” and the “wisdom of the crowd” by reading some Clay Shirky – – here and here.

If you haven’t received two peer reviews from classmates on your sandbox/Wikipedia draft, let me know!

For Tuesday (11/7)

For Tuesday, let’s read an excerpt from Pierre Levy’s “Collective Intelligence.”  And, listen to James Suroweicki talk about the “wisdom of the crowds.”

By Tuesday, you should have a draft of your Wikipedia edit/article in your sandbox.  (I think it’s easier, if you’re editing an existing page, to copy the whole existing article to your sandbox and add your edits there.)  Before you begin moving your article/edits to a live Wikipedia page, you’ll need some peer review.  (See Week 9 on our course dashboard.)

There are three ways to get feedback on your edit/page before moving from sandbox to Wikipedia:

  • feedback from classmates.  See the instructions (again, on “Week 9” under “Peer review and copy edit”) on our dashboard.
  • feedback from content experts.  To solicit this feedback, click on the “Get Help” button in your sandbox and choose a content expert to peek at your work.
  • feedback from other Wikipedia student-editors.  To do this, go to Intertwine and click on the button that says: “Peer Review Session.”  Sign up for a peer review session.

Nota Bene: You will need two of these forms of peer review before you move anything to the live version of your Wikipedia page. Get started with peer review now – – to avoid last-minute difficulties.

For Thursday (11/2)

For Thursday, we’ll meet in the computer lab (HUM 401) to experiment with not reading  Horatio Alger (or any author).

To prepare for not-reading:

  • first, open up a document or grab a pad and pen to take notes on each step in our not-reading.  You should also save interesting Voyant results and Ngram views.
  • check out the Wikipedia page on Alger so you can get some sense of who he is and what his books are like.
  • head over to and download the text file for one of Alger’s novels. (I’ve already started on The Train Boy – – so you’ll have to choose a different novel.)
  • clean up the text file by eliminating all of the headers and footers and extraneous text, such as publication or publisher info, ads, etc.
  • upload your clean text as a .txt file to our shared Alger folder on Google and to Voyant Tools.
  • analyze the Alger text with as many Voyant tools as you can.  Keep notes on what you discover.  Since we already know something about Alger from Wikipedia, try to use this information to locate patterns in the novel.
  • next, download/upload all of the texts in our Alger folder to Voyant Tools.  Test your patterns against this larger corpus.
  • finally, explore the wider contexts for these patterns through Google’s Ngram Viewer.

When you’ve finished not-reading your Alger novel, write a reflective blog post that answers a couple of questions as fully as possible: what did you learn about your novel through your distant reading? what did you learn about distant (and/or close) reading by not-reading Alger?  Use images and charts from your Voyant/Ngram analyses to illustrate your insights.

For Thursday (10/26)

For Thursday, we’ll meet in HUM 410 – – the computer lab.

You should be starting to draft your Wikipedia article in your sandbox.

And, based on the computational textual analysis of your corpus (e.g. Voyant tools analysis), use Google’s Ngram viewer to contextualize your corpus and research questions via Big Data!

For Tuesday (10/24)

How might “Big Data” change the way we study things in the humanities? For Tuesday, let’s talk about Dan Cohen’s view of things in his essay, “Searching for the Victorians.”

In the meantime, write a blog post describing Phase II of your Voyant experience.  As you used questions inspired by Hoover’s essay, what new things have you noticed about your corpus? about the Voyant tools?  Can you describe a hypothetical research project based on Voyant tools?

In the wiki-world – – you should have collected five or six good sources and posted these – – with citations – – in your wiki sandbox.  This week, you want to start drafting your Wikipedia article/edits in your sandbox.

For Thursday (10/19)

On Thursday, we’ll meet in the computer lab (401).  Come to class with the following:

  • a text or corpus of texts you’d like to analyze via computational textual analysis (e.g. Voyant) and at least two questions generated by our exercise with Hoover’s essay on Tuesday.
  • five or six sources for your Wikipedia page project.  These should be entered into your sandbox.
  • take a look at Week 8 on our Wikipedia project dashboard.  On Thursday, you’ll start drafting your page and/or page edits.

For Tuesday (10/17)

Let’s continue our exploration of computational text analysis by reading David Hoover’s “Textual Analysis.”

A couple of other things to keep on your docket:

  • throw up a blog post about your Voyant reading of the text you looked at last Thursday.  Some questions to consider: what kinds of patterns did Voyant help you see in the text? which of the Voyant tools seemed most helpful and why? what kinds of things did Voyant not show you about the text you analyzed? (Here’s an account of how James Baker used Voyant to analyze a huge corpus of British political cartoons.  And, here’s a whole gaggle of Voyant-inspired projects worth perusing.)
  • you want to find five or six sources for your Wikipedia editing project.  Enter the texts and their bibliographical citations in your sandbox and use a sentence or two to explain why/how they’ll be helpful to your editing work.