Social Media

Posts about social data like Twitter, Facebook and their respective APIs.

Recent posts

Mapping GeoJSON On Github

I’ve been hoping to tinker with Github’s new mapping service since the company announced it earlier this month. Turns out it’s quite easy. You just commit a GeoJSON file to your repo, and voilà.

The points on this simple map represents the location of each car2go I’ve rented (excluding those in Austin, Texas). Surprise, they’re mostly clustered in our neighborhood:

car2go locations

This is a simple as it gets. The service also allows other data types, like polygons, for example. Tomorrow I’ll try a more interesting data set, maybe DC property parcels or 311 calls locations. And I’ll experiment with the Github docs to see how I can customize the icons and design. We’ll see…

BTW: Github is using MapBox to create its custom map base layer. Read more about that here. And thanks to my co-worker, Chris Groskopf, whose csvkit suite makes it super easy to convert basic data files into GeoJSON.

Tracking Check-ins With Foursquare Time Machine

Location-based service Foursquare recently released a new feature allowing users to track their past checks by location, venue type and other metrics The browser app visualizes check-ins in sequential order, creating a colorful map and ultimately a personalized infographic.

Apparently, I’ve checked in on foursquare more than 2,400 times — so mine took a bit — but the end result is (slightly) interesting:

foursquare-the-next-big-thing

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Charting Tweets At #UNITY12

Last week I attended the UNITY journalism conference in Las Vegas, and during my stay I ingested more than 9,000 tweets that had the #UNITY12 hashtag. This line chart shows how the traffic ebbed and flowed each day:

As of dinnertime Saturday, when I stopped collecting the tweets, these attendees were the most prolific users of the hashtag: @NABJDigital (164 tweets), @sandhyadirks (136), @emmacarew (118), @joshstoffregen (102), @VictoriaLim (98), @DorisTruong (88), @webjournalist (77), @L2theS2theV (75), @barbaradozetos (70), @cecepmarshall (69).

Download the data, and let me know what you find.

Visualizing the MIT-Knight Civic Media Conference

I’ve spent the last few days in Boston, helping the Knight Foundation visualize data about attendees at its Civic Media Conference. Here is some of that work, which Knight has posted on its blog:

First, I wanted to know when people applied for the Knight News Challenge on networks, the winners of which were announced yesterday. Apparently some of the applicants are procrastinators:

This morning I charted more than 2,600 tweets posted with #civicmedia hashtag yesterday. Tweets by the hour:

Tweets by the minute:

And the people who posted most with the hashtag:

I also spent some time looking at the demographics of the attendees:

By state:

By domain name type and gender:

Some of the visualizations focused on the panel discussions. For a panel featuring DC’s HomicideWatch, I charted five decades of homicides in the city:

And for a session featuring Paul Salopek, a reporter planning to spend years walking the historic path of human migration from Asia to South America, I mapped migration by country last year:

Ranking TechRaking Tweets

Dozens of technologists and journalists today descended on Google’s beautiful Mountain View, Calif., campus for a discussion about technology and journalism. The conference, organized by the Center for Investigative Reporting, led to some prolific tweeting, as one might expect.

I used a simple script to ingest the 1,500-plus tweets with the search API into a sqlite database. This chart, made with Google Docs’ chart tools (when in Rome…), shows the top 25 most prolific tweeters (as of 4:30 p.m. pacific) who used the #techraking and #techrakingcir hash tags.

Congrats, Ian Hill, you top the list (which includes, I think, some spammers):

This is just a quick chart made in a rush. Feel free to download and check out the pipe-delimited data for yourself: #techraking | #techrakingcir. Send me your visualizations or thoughts, and I’ll post ‘em here. See the full list of Twitter user counts here.

Use Calendar Heat Maps to Visualize Your Tweets Over Time

Following Nathan Yau’s excellent tutorial for creating heat maps with time series data (he used vehicle accidents by day for a year), I visualized 3,559 of my tweets back to March 2009.

These maps, created with a modified R script from the tutorial, show how often I sent tweets (both personal and RT), with darker shades representing more activity. It’s fun to go back to the dark days and recall what sparked flurries of tweets:

Visualizing Foursquare, Pt. 2

This morning I posted a quick map illustrating my 1,100 check-ins on Foursquare during the last two years. I made it using TillMill, an open-source application for creating interactive map tiles.

This version was made in OpenHeatMap (larger symbols represent more check-ins). Clearly my Foursquare usage increased after I moved from Austin to DC last year: 

Thanks to Pete Warden, who created the tool. He helped me structure my field headers so the application would recognize the geo data for each check-in. Documentation here.

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Visualizing Foursquare

I’m generally obsessed with Foursquare, the location-based service that allows users to broadcast their travels to friends. I’ve checked in more at more than 1,100 places since joining the service in February 2010, apparently more often on weekends:

But not so much in May:

And on three continents:

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