Re-reading

Here's something you won't find in my resume or portfolio.

WIRED published issue 1.01 in 1993. I was 12 years old.

The magazine adopted Marshall McLuhan as its patron saint. At that point, I had no idea who McLuhan was, but I did read the magazine religiously, and it probably shaped my world view more than anything else. The magazine was obsessed with the "new" (new economy, new technology, new media, new politics, new policy, etc.) and I was drawn to the techno-utopian vision.

It was an exciting time, with modems and CD-ROMs…

My family did own a modem, and I spent a lot of my time online. First Prodigy (my password today is a variant of that very first—mandatory—one) and then AOL. Consumer electronics were exciting, but so were undersea cables, satellite phone networks and shotgun sequencing methods.

…not to mention digital cameras (that took floppy disks!).

The ads that ran with the magazine are amusing to look back at, but the content was surpisingly prescient. WIRED would regularly run 8,000-word cover stories, and the focus was rarely on products. Articles like William Gibson's "Disneyland with the Death Penalty" (on Singapore) examined the intersection of the digital and physical worlds.

I wanted to visually organize the magazine to re-read it.

Today, the archive is a mess, and traversing it requires browsing one issue at a time. I wanted to quickly (and somewhat randomly) read articles from various issues.

Clicking on an issue row will open an article in a new window

One thing that I remember distinctly are the covers.

The Bill Gates cover is iconic, but as a whole, the covers were memorable because of their colors: generally fluorescent, vaguely Dutch, and distinct from everything else at the time.

I wrote a script to download all the covers, and then ran them through a color analysis library to pull out the predominant scheme. That becomes the basis for the navigation.

And, WIRED always introduced me to new words and ideas.

The 90`s were full of neologisms, and WIRED captured them in the glossary.

Using node.js, Python and MongoDB, I wrote a set of scrapers to go through the archive and pick up relevant keywords. These keywords are featured as you scroll through the issues.

Take a look.
Re-discover WIRED with me.

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