Exploring Google Maps to Find Sesame Street

Children's educational television shows make everyone a bit nostalgic, regardless of when one grew up or which particular show was their favorite (I'll always be a bit partial to Ringo Starr and George Carlin as the conductor on Shining Time Station). But with the characters of these shows becoming more fully integrated with the brands they represent, a seemingly endless number of opportunities are available to promote one show over another.

New School v. Old School, Dora v. Oscar

Using the traditional Floatingsheep method of comparing Google Maps references to a number of keywords in order to highlight where one keyword is prevalent over many others, we've mapped references to Sesame Street classic Oscar the Grouch and 21st century bilingual girl-wonder, Dora the Explorer.

The homogeneity of references can only mean one thing: because of her connection to a younger, presumably more hip and technologically adept fan base, Dora has cornered the virtual market of Google Maps. Alternatively, we could chalk this up to the lingering ambiguity of where exactly Sesame Street is.

Regardless of this, Oscar is likely in a trash can somewhere complaining about the biases of our method and how maps don't really represent reality.

Mapping Flickr

Today's map is a visualisation of all 34 million geotagged Flickr images. The data were kindly collected by Eric Fischer and then aggregated to the country-level (an operation that took our computer about three weeks to process!).

You can see that user-generated images in Flickr display similar geographies to other types of user-generated content (e.g. Wikipedia). In the next few weeks, we'll upload some variations of this map. These results aren't necessarily surprising, but do just reinforce findings that subjects of user-generated content are highly concentrated in only a few parts of the world.

New Paper: Volunteered Geographic Information and the Haitian Earthquake

Our paper on the use of volunteered geographic information in response to the Haitian earthquake, co-authored with Sean Gorman of FortiusOne, has just been published in World Medical and Health Policy.

Be warned. This is an educational moment. You might learn something. After all it can't be all fun and correlations. The abstract and links to the paper are below.

Volunteered Geographic Information and Crowdsourcing Disaster Relief: A Case Study of the Haitian Earthquake
by Matthew Zook, Mark Graham, Taylor Shelton and Sean Gorman
World Medical & Health Policy Vol. 2: Iss. 2, Article 2.
Available at: http://www.psocommons.org/wmhp/vol2/iss2/art2

This paper outlines the ways in which information technologies (ITs) were used in the Haiti relief effort, especially with respect to web-based mapping services. Although there were numerous ways in which this took place, this paper focuses on four in particular: CrisisCamp Haiti, OpenStreetMap, Ushahidi, and GeoCommons. This analysis demonstrates that ITs were a key means through which individuals could make a tangible difference in the work of relief and aid agencies without actually being physically present in Haiti. While not without problems, this effort nevertheless represents a remarkable example of the power and crowdsourced online mapping and the potential for new avenues of interaction between physically distant places that vary tremendously.

Or, if you don't have institutional access, you can find our paper here.

Also two Floatingsheep-style maps before and after the earthquake are below (and are in the paper). By the way, Haiti is on the western portion of the island of Hispaniola, the Dominican Republic is on the eastern side.

Cyberscape Before the Earthquake

Cyberscape After the Earthquake

Obesity, Beer and Christianity: Or Correlation does not equal causation

One of the basic rules in statistical analysis is that correlation does not equal causation. But in the hot days of a Kentucky summer one often gives into temptation, especially if the graphs look good.

We therefore leave it to our readers to jump to the unsupported causal relationship. Sorry, you'll have to work/think through this one yourself.

Y-axis: Percentage of a state's population that is Obese
X- axis: Number of Placemarks with
Keyword Beer / Total number of Placemarks
Bivaritate correlation (-0.45)

Y-axis: Percentage of a state's population that is Obese
X- axis: Number of Placemarks
with Keyword Christianity / Total number of Placemarks
Bivaritate correlation (0.729)

Although the nature of the graphs invite one to believe that Christianity is somehow responsible for obesity this is no doubt a spurious correlation. It is well known that obesity and religious practice are strongly related to income. One can see this in which states are clustered at the extremes.

Why places with a high percentage of beer reference are less obese is a bit more difficult to explain.

Don't worry, we have more. We particularly like relationship between placemarks with the terms falafel and feminist.

Recapping our Predictions for the World Cup or Why Floatingsheep rocks!!

Now that the dust has settled after the world cup it is time to reflect on our predictions. Our language sensitive ranking system based on geo-coded references to football/soccer correctly identified three out of the final four countries in the world cup. The only error was predicting England over Germany. Although one can suspect foul play from the English member of the Floatingsheep collective, there is a methodological explanation as well.


Our searches are limited to land, as there are very few placemarks in water. While this works in a general sense, it does exclude references to football by a country's aquatic citizens. While this is miniscule in most cases, the case of Paul the Octopus suggests that Germany may have a sizeable underground (or better phrased, underwater) population of football enthusiasts that were missed in the data.

Or maybe Mark just cooked the data so England would win. Still you could have done much worse if you used our predictions.

After all, using our system we did make about $17,000 dollars via offshore betting. Unfortunately, we have already spent it all on gumdrops, Botox and aquavit. Clearly we're just not cut out for life in the fast lane.