I’ve just come across some important blog essays by David Gaertner. One is Why We Need to Talk About Indigenous Literature in the Digital Humanities where he argues that colleagues from Indigenous literature are rightly skeptical of the digital humanities because DH hasn’t really taken to heart the concerns of Indigenous communities around the expropriation of data.
Bill Robinson has penned a nice essay Marking 70 years of eavesdropping in Canada. The essay gives the background of Canada’s signals intelligence unit, the Communications Security Establishment (CSE) which just marked its 70th anniversary (on Sept. 1st.)
The original unit was the peacetime version of the Joint Discrimination Unit called the CBNRC (Communications Branch of the National Research Council). I can’t help wondering what was meant by “discrimination”?
Unable to read the Soviets’ most secret messages, the UKUSA allies resorted to plain-language (unencrypted) communications and traffic analysis, the study of the external features of messages such as sender, recipient, length, date and time of transmission—what today we call metadata. By compiling, sifting, and fusing a myriad of apparently unimportant facts from the huge volume of low-level Soviet civilian and military communications, it was possible to learn a great deal about the USSR’s armed forces, the Soviet economy, and other developments behind the Iron Curtain without breaking Soviet codes. Plain language and traffic analysis remained key sources of intelligence on the Soviet Bloc for much of the Cold War.
Robinson is particularly interesting on “The birth of metadata collection” as the Soviets frustrated developed encryption that couldn’t be broken.
I’m blogging now at Three dimensional dynamic data exploration for DH research. This the project that brought me to Hamburg for these three months so most of my blog entries will be on that site. The project is developing ideas for a next generation visualizations for the humanities.
3quarksdaily, one of my favourite sites to read just posted a very nice essay by Sanjukta Paul on Where Probability Meets Literature and Language: Markov Models for Text Analysis. The essay starts with Markov, who in the 19th century was doing linguistic analysis by hand and goes to authorship attribution by people like Fiona Tweedie (the image above is from a study she co-authored). It also explains markov models on the way.
On the ethos of digital presence: I participated today in a panel launching the Italian version of Paolo Sordi’s book I Am: Remix Your Web Identity. (The Italian title is Bloggo Con WordPress Dunque Sono.) The panel included people like Domenico Fiormonte, Luisa Capelli, Daniela Guardamangna, Raul Mordenti, and, of course, Paolo Sordi.
I’ve been meaning to blog this 2014 use of Voyant Tools for some time. Which Words Are Used To Describe White And Black NFL Prospects?. Deadspin did a neat project where they gathered pre-drafting scout reports on black and white football players and then analyzed them with Voyant showing how some words are used more for white or black players.
Feminist Frequency has posted an excellent Speak Up & Stay Safe(r): A Guide to Protecting Yourself From Online Harassment. This is clearly written and thorough discussion of how to protect yourself better from the sorts of harassment Anita Sarkeesian has documented in blog entries like Harassment Through Impersonation: The Creation of a Cyber Mob.
As the title suggests the guide doesn’t guarantee complete protection – all you can do is get better at it. The guide is also clear that it is not for protection against government surveillance. For those worried about government harassment they provide links to other resources like the Workbook on Security.
In her blog entry announcing the guide, Anita Sarkeesian explains the need for this guide thus and costs of harassment thus:
Speak Up & Stay Safe(r): A Guide to Protecting Yourself From Online Harassment was made necessary by the failure of social media services to adequately prevent and deal with the hateful targeting of their more marginalized users. As this guide details, forcing individual victims or potential targets to shoulder the costs of digital security amounts to a disproportionate tax of in time, money, and emotional labor. It is a tax that is levied disproportionately against women, people of color, queer and trans people and other oppressed groups for daring to express an opinion in public.
How did we get to this point? What happened to the dreams of internet democracy and open discourse? What does it say about our society that such harassment has become commonplace? What can we do about it?
Hashtagify.me is a neat site that tracks hashtags in Twitter. For example, here is what they have on #GameGate. They show the other hashtags that your hashtag connects to (like #NotYourShield) and you can get a trend line.
The trend makes it look like #GamerGate is going down, but I don’t trust their projection.
All of this is free. They also have a Pro account, but I haven’t tried that.
Thanks to Brett for this.
Elika Ortega in a talk at Experimental Interfaces for Reading 2.0 mentioned two web sites that gather interesting material traces in digital books. One is The Art of Google Books that gathers interesting scans in Google Books (like the image above).
The other is the site Book Traces where people upload interesting examples of marginal marks. Here is their call for examples:
Readers wrote in their books, and left notes, pictures, letters, flowers, locks of hair, and other things between their pages. We need your help identifying them because many are in danger of being discarded as libraries go digital. Books printed between 1820 and 1923 are at particular risk. Help us prove the value of maintaining rich print collections in our libraries.
Book Traces also has a Tumblr blog.
Why are these traces important? One reason is that they help us understand what readers were doing and think while reading.
Tyler Trkowski has written a Feature for NOISEY (Music by Vice) on Rap Game Riff Raff Textual Analysis. It is a neat example of text analysis outside the academy. He used Voyant and Many Eyes to analyze Riff Raff’s lyrical canon. (Riff Raff, or Horst Christian Simco, is an eccentric rapper.) What is neat is that they embedded a Voyant word cloud right into their essay along with Word Trees from Many Eyes. Riff Raff apparently “might” like “diamonds” and “versace”.