Gabe Sawhney

[This update on my Twitter cluster visualization project is also the final report for the independent study I’ve been doing on infoviz. I’ll definitely pick up this work again soon, but not in the next couple of weeks. A previous post with some of my early tests and rationale is here. A walkthrough on how to get started making these is here.]

For the past few months I’ve been absorbing lots about information visualization, and in the past four weeks I’ve been doing a bunch of work specifically on visualizing clusters based on the Twitter network. The goal of this is described in a previous post. Along the way, I’ve learned a weird bunch of other things: tuning MySQL performance, the advantages of the Google Social Graph API over the Twitter API, how to get around the fact that many of OCAD’s lab computers are still running OS 10.5, how to make a screencast, etc. I want to take this work in a bunch of other directions (and will, once I’ve dealt with my other deadlines). Here’s some of the more interesting maps that I produced along the way: Continue reading →

I like step-by-step walkthroughs. They’re task-oriented and context-specific, not universal like conventional documentation. They’re good because no matter what it is I’m doing, someone else has certainly done it before. They’re also good, because when I take the time to figure something out, it’s nice to have a record of it in case I need to do it again. I make them for myself often; generally just a record of ‘Terminal’ commands I used to get something done (they’re more complicated when there are GUIs involved).

So, here’s a walkthrough of how I made my Twitter maps. I’ve tried to keep it simple, but you’ll need to know a bit of MySQL to make this particularly useful. Continue reading →

I’ve seen lots of maps of online social networks. They’re nifty, but often either ugly or messy or useless. But I came back from Strata really impressed with LinkedIn’s InMaps. The layout of the maps is pleasing, but more importantly, they use cluster analysis to demonstrate something that’d be harder to do if not visualized. If you have a LinkedIn account and haven’t tried InMaps, do.

In InMaps, clusters tend to represent companies or communities-of-interest. I wondered what they might represent if I fed it the network of people that I follow on Twitter. Continue reading →

Just over a year ago, Alex de Freitas and I collaborated to produce ‘Unseen Geographies,’ a tool to assist Alex with his research on the geography of free wifi. Alex was experimenting with Twitter as a research tool, to conduct short interviews with people about how and where they found and used free wifi. Twitter’s interface (nor that of any of the clients) was suited to what Alex wanted to do, and so we came up with a plan (in an all-night cafe near NYU, if I remember correctly), secured a small research grant from the MEIC, and built it. (It’s a private tool, so I can only share screenshots.) Continue reading →

[This post is a bit late; I went to Strata two-and-a-half months ago. It was there that I had the conversation (with Tony Thompson; thanks) which finally inspired me to start this blog.]

Not long into my research on information visualization, I came across the announcement for the Strata conference. I’ve fascinated with “big data” since I was introduced to it (though not the term) in Marc Davis‘ keynote at the Mobile Nation conference in 2007. It’s additionally fascinating to me now, because I’m thinking so much about scale. While not exactly pitched this way by O’Reilly, it was widely seen as the first big/broad conference on big data, and people remarked throughout the conference that this was the “first time” that “nearly everyone” was in the same room at the same time. Continue reading →

Greg invited me to participate in an event in the sLab Explorations series, last Wednesday (March 30). I showed some previous work, talked about the Strata conference, and showed just a few images from the work I’m currently doing. After me, Patricio Davila and Sara Diamond also spoke. The turnout was great; and a diverse mix of people. (Thanks, Greg!)