To answer the question we took advantage of the variety of metadata made available through Twitter streaming API. We’d already mapped the location of Tweets from mobile devices when we did our original analysis and now we wanted to add an origin to the destination data. To get a rough proxy for the home of each Tweet we queried the profile location for each user then connected it to the location for where the Tweet was made. Then generated lines to connect the two, calculated a distance for each and gave the time stamp of the Tweet to the line connecting the points.

The results are pretty interesting (warning the live map has a lot of data a takes a bit to load). Below is an image of the map showing all 12,244 trajectories:

Each trajectory is color coded by it’s length – dark orange being longest and light orange being shortest.

One of the nice things about GeoCommons is when you upload data it will automatically calculate statistics for your data. In this case the statistics tell an interesting story. The range of trajectory lengths went from “0″ (user tweeted from home) to 33,296 km (user went from Los Angeles USA to Auckland New Zealand).

The average (mean) Tweet trajectory was 944 km. This is a little misleading since the standard deviation for the sample is so high – 3544.63. Meaning there was a lot of variation in the values with really long trips like LA to Auckland which skews the distribution. In this case a better indicator is probably the median, which is the middle number in a rank order distribution of the values (1,2,3,5,10,10,11,12,12,13,135 -> median = 10). For the Twitter trajectories the median was 18 km. Which means the vast majority of people stayed fairly close to home while a small minority went very far away for their Black Friday activities. You can see the same pattern in a histogram of the data.

As well as in the map when you filter down to trajectories shorter than 166 km – there are a bunch!

The vast majority of Tweet trajectories fall in the bin between 0 and 160 kms or so. If we really want to get geeky about it – the distribution has power law or exponential characteristics often seen in small world networks. The majority of our connections are local but a few global connections is what allows information to efficiently span the globe at warp speed – six degrees of speration – the Kevin Bacon Game etc etc. It does seem to really get at the essence of Twitter as a hyper efficient broadcast channel for the globe.

* Many thanks to @BillfGreer and @cwhelms for help with the data munging!

You can get your check-in feed as RSS, KML and ICS from the feeds page.

From the Finder! API you can register URLs.  Below is a sample curl command to register a KML feed of your Foursquare check-ins.

curl -i -X POST -u “yourusername:yourpassword” -d “overlay[wild_url]=http://feeds.foursquare.com/history/yourkmlfeed.kml” http://finder.geocommons.com/overlays.xml

Replace “yourusername:yourpassword” with your GeoCommons username and password and “http://feeds.foursquare.com/history/yourkmlfeed.kml” with your Foursquare KML feed.

By default your layer is not shared in Finder!, if you want to make a map though you have to share it.  In order to share it go to Finder and login.  Once logged in press “My Layers” and share your layer there.  If you ever decide you no longer want to share your check-in feed you can mark it “not shared” here as well.

Once your layer is uploaded and shared you can create a map.

I embedded the map I made in my personal blog’s about page.  To embed your map click on the “Details” button while viewing the map and then click on “Do you want to embed this map in your website?”  Copy the code that appears and paste it into the HTML of your blog or other website.

If you enjoy playing Foursquare and want to share your feed try this out.  For more information on the Finder! API checkout it out here. Also if you ever happen to visit us in the GeoCommons’ office, check-in it is an order from the Mayor.

Harvard launched AfricaMap. The map is based on the Harvard University Geospatial Infrastructure (HUG) platform and was developed by the Center for Geographic Analysis.  AfricaMap, a OpenLayers-based app, aims to expand existing initiatives for globally sharing spatial data and technology. 

Google Maps created a fun quiz where you get to test your geographic puzzle solving skills. To play the quiz, you have to rearrange letters in a map, using visual clues in the form of a Panoramio photograph, to spell a world capital or U.S. state capital.

The USGS National Geospatial Program Office launched a new version of The National Map website. Revisions include The National Geospatial Program and The National Map web site.

Discussions about the auto industry bailout have been percolating the blogosphere. How would this affect auto industry workers? CNN created an interactive map showing the number of auto industry jobs in each state.

The use of GIS for natural disasters is now trickling over to emergency preparedness. The World Vision International, a faith-based disaster aid organization, is beginning to embrace GIS. The main mission of the organization is to ‘overcome poverty and injustice by reducing the impact of natural disasters with area development programs that concentrate efforts with long-term commitment to maximize their impact.’ Because there is a direct correlation between poverty and areas prone to natural disasters, World Vision International will use GIS to help save lives and prevent loss of life.

The Coalition of Geospatial Organizations (COGO) is now official. A meeting was held this week at the ESRI User’s Conference in San Diego, where organization members voted on their new officers. Currently the coalition has 11 organization members including, the Cartography and Geographic Information Society, the GIS Certification Institute and the American Congress of Surveying and Mapping.

Geospatial professionals are integrating with social networks. Apparently, social network creator Ning has about 22 members and is steadily growing in their Geospatial Professionals Network. Fellow professionals are encouraged to join and engage.

Finally, as the Olympics get underway, we want to say good luck to Director of Operations Matt Madigan, who is currently in Beijing coaching the women’s quad sculling team.

ESRI released their downloadable application, ArcGIS Explorer 480, this week. The upgraded version still offers the same basic function of geoprocessing services, but with major improvements such as KML improvements and increase in performance.

Nokia acquired Plazes, an LBS social mapping network. Plazes provides updates of friends’ activities in a find me/follow me type of service. The social mapping application will take Nokia one step closer to “bringing people and places together” and also acknowledges the rise and demand of LBS.

Microsoft and Virtual Earth launched a program that allows state and local governments to share their imagery, called GoVE. All of the imagery from these governments, municipalities and aerial photographers gets sent to Microsoft, which in turn is published by Virtual Earth.

Before the GeoWeb came into mainstream popularity both Microsoft and Yahoo! had mapping applications. Microsoft offered their browser based Terraserver which hooked up USGS imagery for the map tiles. Microsoft launched Terraserver in June of 1998 – practically prehistoric.

Microsoft had also been active in the mapping space with products like MapPoint (both desktop application and web services). Yahoo! also was an early adopter of mapping applications in conjunction with their local search destination (although I completely failed at finding a date for when they first added maps). Despite the early adoption of web based mapping applications by Yahoo! and Microsoft it was arguably the launch of Google Maps in 2005 that jump started both the GeoWeb and the mash up craze.

Shortly after Google Maps launched, Paul Radamacher hacked the application to allow it to display Craig’s List rental listings on the Google slippy map. Shortly there after Adrien Holovaty followed suit mashing up Chicago crime statistics with Google Maps. Google quickly released an API to allow developers to do the same thing seamlessly and we were off to the races. Microsoft quickly created Virtual Earth and Yahoo! pushed out Yahoo! Maps. Microsoft created compelling innovations with birds eye imagery and Yahoo! launched several popular GeoWeb services like free geocoding and Flash based mapping APIs.

Microsoft Collections

Through all these innovations there was a constant one way flow of content creation – developers could create unique maps and users could view them. Microsoft changed this when they launched Collections May 23, 2006:

Collections. Social networking functionality allows customers to create lists of favorite landmarks and locations, attach personal photos and save them to a Scratchpad. Collections can be saved, recalled later, “permalinked,” and shared with friends and community in e-mail or through their MSN® Spaces blog.

While not well publicized the “Collections” concept fundamentally changed the work flow for creating maps. No longer did you need to be a developer or GIS pro to create a basic map and share it with other people. The Virtual Earth folks even gave users a decent amount of cartographic power and options:

Customized pushpins. A pushpin is essentially a marker indicating points of interest on a map view. A customized pushpin can easily be added with a simple right click, anywhere on a map, which will display a small red dot and a pop-up menu. A pushpin title or note of up to 200 characters can be added that will appear with the pushpin whenever a mouse hovers over it. Pushpins can easily be edited or deleted. When a pushpin is removed, whether customized or standard, the remaining pushpins will be automatically renumbered.

2-D drawings in Collections. Users can add lines and drawings in a variety of colors, shapes and styles to personalize their Collection. They also can draw lines and shade areas that they want to mark on the map, such as for marking a running or bike trail, or neighborhood boundaries).

MyMaps

Despite the potential of the innovation the new functionality did not get much coverage in the press or massive levels of adoption. The TechCrunch article on it was lumped in with other new features from Yahoo! Maps.

Just short of a year later Google launched Google MyMaps on April 4th 2007 to big headlines across the blogs, including MyMaps being the death knell of popular map mashups like Platial, Frappr and Tagzania.

Fundamentally the functionality and features of MyMaps was not remarkably different than Collections, but the buzz around it was at least ten fold. So why was the attention so skewed towards Google for fundamentally the same innovation Microsoft had launched a year earlier? A few guesses:

MapMixer

Yahoo! was not too far behind launching their own map creation application, Yahoo! Mapmixer on September 13th 2007. Mapmixer took a different angle on map creation by allowing users to put static maps on top of the Yahoo! Maps applications. For instance after the Buscan oil spill in the San Francisco Bay last year I made a lot of calls trying to get the raw data on the location of the spills, for GeoCommons, but had no luck.

I did find a PDF with a map of the oil spills so I saved it as a PNG then uploaded it to Yahoo Mapmixer and they took me through three easy steps to georeference the map on Yahoo! Maps. The user experience I thought was the best of the three and there were lots of great social features for me to give a short description of the map and for other users to comment on the map. Although much like Microsoft the application did not generate lots of buzz as with Google MyMaps, and the gallery only features 38 user submitted maps today. Interestingly, in concept, it is quite similar to Microsoft’s MapCruncher, although it is a download and supports a wider variety of raster based formats that must already be georeferenced.

Since the launch of map creation applications by the three big players there have been two noticeable waves of enhancement 1) support for external data and 2) collaboration features. Microsoft put themselves out as being the first to support loading KML, “The October 07 release of Live Maps was the first to support KML viewing and import to Collections”. November 27th 2007 Google added KML, KMZ and GeoRSS support to MyMaps. Google followed this up with social features, like commenting, rating and open collaboration invitations for MyMaps.

Performance Trials

That covers features and functionality from a historic evolution stand point, but how do they perform? We did a very informal, one user, stress test. Create push pins as quickly as possible and see when the map application maxes out or gets sluggish. For Yahoo! Mapmixer this was pretty easy. You can overlay one picture or map onto the application, so you max out at one.

In the process of loading and georeferencing the image you get speedy performance and predictable response times. For MyMaps and and Collections we had a bit more to stress. We’ll start with Collections where we created 200 push pins with good response time then got the following message “You cannot add more than 200 items to a collection. To add more items, create another collection.”

When we went with the same test on MyMaps,we did high rate push pin creation and after about 30 the system got a bit sluggish, and sometimes it would create a listing for a pushpin on left hand pane but not create the push pin on the map. The caveat here is we were doing this high speed, and when we slowed down to a more deliberate pace the system handled it fine.

MyMaps also maxes out at 200 push pins on the map, but instead of providing a warning it generates a pagination for a continuing set of push pins. So when you click on the first page you get a map with the first 200 push pins and when you click on the second page you get the next 200 push pins on a new map in the same browser and tab. Oddly it stops at 820 push pins and starts back over at the number one but you can keeping adding push pins to the map.

What’s Next?

That pretty much wraps it up for a comparison of the big three, how they evolved in a competitive environment, and a very ad hoc test of their limits.

I believe the most interesting part will be where they evolve to next. What is the next set of functionality that will distinguish one from the other? Can Microsoft or Yahoo! introduce the next killer functionality that will catch up to 7 million maps that have been created with MyMaps?

Romney vis McCain: Michigan primary vote

Note: Brighter hues = Higher vote count, Darker hues = Lower vote count

This is Romney’s first win (not including his win in the Wyoming primary) and probably saved him from dropping out of the primaries after finishing 2nd, both in Iowa and New Hampshire. McCain and Huckabee finished 2nd and 3rd respectively. With Romney’s win in Michigan, the GOP has no clear cut front runner. Romney got nearly 38.9% votes (~337,700), to McCain’s 29.7% (257,400), followed by Huckabee at 16% (~139,600).

DNC (Democratic National Committee) decided to punish Michigan for violating primary rules by moving forward its primary date. They stripped Michigan of all its delegates for the National convention. As a result, both Obama and Edwards withdrew their names, while Clinton’s name remained on the ballot and she won the primary. According to some, Clinton would have won the primary anyway.

Clinton vis Mr. Uncommitted: Michigan primary vote

Note: Brighter hues = Higher vote count, Darker hues = Lower vote count

Interestingly many who wanted to support either Obama or Edwards voted “Uncommitted”. Clinton won more than 55% vote (~327,300) compared to 40% vote for Mr. “Uncommitted” (~236,900). And much of the “Uncommitted” vote came from African Americans and young voters according to the exit polls. This does not bode well for the Clinton camp, as the Democratic primaries move south where African-Americans are a major constituency. More on this in the future blogs.

In the meanwhile you may want to explore all of the maps shown above at Geocommons. Search with keywords “Michigan” or “Primary” to discover dynamic, interactive maps with zoom-in and pan.

The spatial distribution showing where McCain won more votes compared to Romney.

The flipside of the above map is the one below showing where Romney won more votes compared to McCain.

Explore the interactive heatmap using pan and zoom here.