What percentage of edits to English-language Wikipedia articles are from local people?

As part of our on-going efforts to explore the geographies of participation in Wikipedia, we have calculated the percentage of local edits to articles about places. In other words, this map illustrates the percentage of edits about any country that come from people with strong associations to that country.

For more on the method that we employed, have a read through the post on "who edits Wikipedia" - in which the data collection efforts have been explained in much detail. The data are undoubtedly somewhat imprecise, but we are confident that they offer us the best overview of the geography of authorship that can be obtained with publicly-available data.

So what do these results tell us?

Unsurprisingly, they show that in predominantly English-speaking countries most edits tend to be local. That is, we see that most Wikipedia articles (85%) about the US tend to be written from America, and most articles about the UK are likewise written from the UK (78%). The Philippines (68%) and India (65%) score well in this regard, likely because of role that English plays as an official language in both countries. But why then do we see relatively low numbers is other countries that also have English as an official language, such as Nigeria (16%) or Kenya (9%)?

We also, interestingly, see relatively high local edit percentages from a handful of countries that don't count English as an official language: Finland (50%), Norway (56%), Romania (54%), and Bulgaria (53%).

Then we also observe large parts of the world in which very few English-language descriptions about local places are created about local people. Almost all of Sub-Saharan Africa falls into this category. The key question is whether these data actually tell us anything meaningful. For instance, just because most edits about the United States likely come from the United States does not necessarily mean that those articles are representative, include a diversity of viewpoints, or fail to exclude people, places, and processes.

But the data nonetheless, in a very broad way, do tell a story about voice and representation. Some parts of the world are represented on one of the world's most-used websites predominantly by local people, while others are almost exclusively created by foreigners, something to bear in mind next time you read a Wikipedia article.

IronSheep 2013

Inspired by the Iron Chef television series, we are holding our second annual IronSheep geo-hackathon.  This year we'll be in Los Angeles, California during the annual AAG conference.

Please click here to register.  Given space constraints of the venue, only folks who register will be able to participate.

The event seeks to mimic the format of the “Iron Chef” television series and challenges participants (grouped into teams with members from diverse backgrounds and skill sets) to produce meaningful analysis and fun, evocative map mash-ups from the same sets of user-generated, geo-coded data within a four hour time frame. The goal is to provide a semi-structured environment where participants can socialize and work in a fun yet socially meaningful project. Participants will be drawn from academic, industry and artistic communities from around the world.

There will be prizes, there will be trophies, there will be gratuitous sheep.

Date: Wednesday April 10, 2013
Time: 5 pm to 9 pm
Location: LARTA (an non-profit innovation hub working with the Southern California tech community) located at 606 S. Olive Street, Suite 650, Los Angeles (a 10 minute walk from the AAG hotels)
Bring: your laptop, software, friends, lovers, geographers, programmers, geo-geeks, ewes, rams and lambs
Don't bring: wolves, Chupacabra or mint sauce as we learned last year they are hazardous (or offensive) to sheep.

We will provide food, beverages, data, internet, prizes and sparkling commentary. And perhaps even present one of the floating sheep collective as a sheep.  But don't count on that last point.

How to Win--suggestions from the first season of Iron Sheep

Location! The Importance of Geo-Data: Mark and Monica at SXSW

For any of our fans who might be in Austin this weekend for SXSW, be sure to check out the panel that Mark and Monica organized this Tuesday. You can check out more info about their panel (along with some visual evidence that they're having fun) below...

What: Location! The Importance of Geo-Data
Where: Sheraton Austin, Capitol ABCD
When: Tuesday, March 12, 11am-noon
Who: Mark and Monica will be joined by Catherine D'Ignazio of MIT and Devin Gaffney of the Oxford Internet Institute. 

The proliferation of location-aware devices and geo-tagged data raises important questions: what will happen as more and more of the content we create online is automatically tagged with locational data? What can we learn from this profusion of geographic information? With this data we can find restaurants, friends and sex partners (a la Grindr.com), visualize inequalities in media attention, develop epidemiological models to predict the spread of diseases, find dissident safe houses in times of political upheaval and coordinate crisis response. But who is contributing data and who is not on the map? How are our social relationships being transformed? What about privacy? What about civic participation? Serious questions are mounting - this panel aims to raise several of them, and explore the transformative power this shift may bring.

The Urban Geographies of Tweets in Africa

This is a quick post containing a few visualisations of information densities in a selection of African cities.

Below, you can find maps of all geocoded tweets published in November 2012 in Accra, Cairo, Dar es Salaam, Cape Town, Johannesburg, Lagos, Tunis, Nairobi, Kigali, Mogadishu, and Addis Ababa.

Look for the information presences and absences; groups of people who are and aren't participating in each city. But also look at the significant differences between cities. Cities like Nairobi, Cairo, and Cape Town are swimming in thick clouds of information, whereas in Mogadishu and Addis Ababa we barely find any digital geospatial information at all. 

If you're interested in why these geographies of information might matter, then check out any the articles at the end of this post. Otherwise, enjoy the maps - and please share any insights you have about any of these cities (or let us know if there are other cities that you'd like to see mapped).

Relevant articles:

Graham, M. 2013. Virtual Geographies and Urban Environments: Big data and the ephemeral, augmented city. In Global City Challenges: debating a concept, improving the practice. eds. M. Acuto and W. Steele. London: Palgrave. (in press).

Graham, M and M. Zook. 2013. Augmented Realities and Uneven Geographies: Exploring the Geo-linguistic Contours of the Web. Environment and Planning A 45(1) 77-99.

Graham, M., M. Zook., and A. Boulton. 2012. Augmented Reality in the Urban Environment: contested content and the duplicity of code. Transactions of the Institute of British Geographers. DOI: 10.1111/j.1475-5661.2012.00539.x  

The Maps of Sheepallenge

In our first annual Sheepallenge competition, teams from around the world (well, parts of it anyways) competed to produce the best visualization using a dataset relating to the seven deadly sins. We've included some of our favorite submissions below, but please feel free to comment and let us know which are your favorites.

In the Animated/Interactive category:
Interactive map of Political Sex Scandals: you must click on the link to get the full scandalous effect
(Montserrat Compa, Jasmine D'Angelo, M. Eiben and​ R. Gustas of Humboldt State University)

Coffee vs. Beer: an animated time-map of Coffee and Beer consumption. (Nathan Barth and Stephen Mangum of Humboldt State University)

We had two Seven Sins Choropleth maps:
http://users.humboldt.edu/eibenm/sheepallenge.html
(Matthew Eiben, Humboldt State University)
http://tiles.mapbox.com/gfs1119/ 
(Gwendolyn Schaefer and Jordan Miller, University of Kentucky)

Animated wrath of god: Zoom and pan through natural disasters caused by sinners (Jeremy Battles, Humboldt State University)

In the Static map category:
Anti-Cartograms: Teriitutea QUESNOT of Université Laval

"Rather than highlighting devilish states, I preferred to adopt a reverse logic by building anticartograms.  These anticartograms are based on the mathematical inverse function (1/x) : the area of each US State is consequently inversely proportionnal to the number of Tweets included in each state.  Moreover, we know that the seven heavenly virtues are not exactly the opposite of the seven deadly sins. Thus, the title of each anticartogram correspond to my own interpretation of each "antideadly sin" (e.g. « Twitter Buddhists » for the anticartogram of the « envy » deadly sin)."

The Bacon Map: Miles Ross, Letha Gimble, and Lars Erickson (Humboldt State University)

"If you want to run far far away from your grassroots vegan friends and join the bacon eating bandwagon you might try moving to a bigger city.  The results from this map revealed that Seattle was the most infatuated with this lardaceous meat, seen by the overwhelming sized bacon strip that has taken over the Pacific Northwest in the map.  Chicago, New York, Boston, Wichita are only a couple of the bigger cities feeding into this fattening fad."

Sinners Across The USA: Tanja Hopmans and Sean Jansen (Humboldt State University)

"Proportional text was created using geotagged Twitter data with tweeted keywords associated with each of the seven sins.  The text represents the maximum number of tweets of the sin, normalized by country, the size of the text represents the number of tweets associated with each sin."

Crunk n' Bible Studies: Boyd Shearer, outrageGIS.com

The goal was to determine the mood of county’s population, whether they were tweeting more about getting drunk or going to bible study. Two groups of geocoded tweets were sampled from DOLLY for the time period June 21 to November 29, 2012. Roughly 8,000 tweets were collected for each population. The “crunk” population was created from tweets that said, “Let’s get drunk,” “Let’s get fucked up,” and “Let’s get crunk.” Minor variations were also added to this population, e.g., “Let’s get crazy fucked up!” The second population was created from tweets that said, “bible study.” Assuming authors meant what they tweeted, a rather unscientific sampling of each population determined an error rate in the sentiment analysis. Approximately 4 out of 100 tweets in the “crunk” population were of a mocking or derisive tone about getting drunk, while 2 out 100 tweets in the “bible study” population were not about studying the bible as illustrated in the following tweet, “Just got asked to go to bible study....no.”

Rich Kids of Instagram: Ryan Cooper and Sonya Prasertong, University of Kentucky

"Our visualization was inspired by the website richkidsofinstagram.tumblr.com, where photos that affluent teens/young adults post on Instagram (as well as their captions) are posted. These photos and captions are often an absurd/over-the-top flaunting of their wealth, posted to inspire envy amongst us lay people. The website is a catalog of these photos, and highlights this strange phenomenon of conspicuous hyperconsumptions represented through social media. By mashing the number of RKOI-based Tweets against median household income we can begin to query deeper questions of income disparities, material consumption practices, and what it really means to #getonmylevel.”

Each of the authors above have won a t-shirt award and a certificate suitable for framing. 

Honorable Mentions
The Good, The Bad and The American: Robert Gustas and Jessica Beck, Humboldt State University

Tweets of Chastity and Lust: James Knoer

In Greed we Trust: Catherine Hoyle, Humboldt State University

Lazy Humidity: Mark and David Cross, University of Kentucky

Seattle, Capital of Greed?: Lila Garcia, University of Washington

Sins Vs. Shows: Derek Ichen, Humboldt State University

The Evil of WalMart and Jersey Shore: Stuart Denoon-Stevens, Cape Town, South Africa

PDF Brochure available here

Congratulations to everybody who participated. The maps we received were fantastic beyond our wildest sheep-filled dreams!

New Special Issue of E&PA: Situating Neogeography

The new special issue of Environment and Planning A on neogeography edited by Matthew Wilson and Mark Graham, and featuring a handful of pieces by members of the Floatingsheep team and other friends of the sheep, is now out and available to download. The complete table of contents is below:

Theme issue: Situating neogeography

Guest editors: Matthew W. Wilson, Mark Graham

Guest editorial
Situating neogeography
Matthew W. Wilson, Mark Graham

Neogeography and volunteered geographic information: a conversation with Michael Goodchild and Andrew Turner
Matthew W. Wilson, Mark Graham

Crowdsourced cartography: mapping experience and knowledge
Martin Dodge, Rob Kitchin

Situating performative neogeography: tracing, mapping, and performing “Everyone’s East Lake”
Wen Lin

Neogeography and the delusion of democratisation
Mordechai (Muki) Haklay

Commentary: Political applications of the geoweb: citizen redistricting
Jeremy W. Crampton

Augmented realities and uneven geographies: exploring the geolinguistic contours of the web

Mark Graham, Matthew Zook

Featured graphic: Mapping the geoweb: a geography of Twitter
Mark Graham, Monica Stephens, Scott Hale

p.s. feel free drop Mark a note if you don't have institutional access to journal and would like email copies of any of the articles. 

Premier League teams on Twitter (or why Liverpool wins the league and the Queen might support West Ham)

Have you ever wondered where Premier League football teams draw most of their support from? Or what the geography of fandom is? We have too, and set about to better understand how Premiership teams are reflected in Twitter usage across the UK.

The Floatingsheep team, with the help of two researchers from the Oxford Internet Institute - Joshua Melville and Scott A. Hale (both of whom did most of the work) - have created a neat interactive map for you to both explore the geography of Twitter mentions of specific teams, and let you explore the patterns of five key rivalries. Click on the screenshot below to be brought to the full interactive map. 

The data used include all geotagged tweets mentioning any of the Premiership football teams and their associated hashtags (e.g., #MUFC or #YNWA) that were sent between August 18 and December 19, 2012. We have only included one tweet per user to prevent 'loud' fans from skewing the results. The users were then aggregated to postcode districts in order to see a fairly fine-grained geography of results. The number of tweeters per district is normalized by the total 'population' of Twitter users based on a 0.25% random sample of all tweets within the UK. 

What do the data show us, you ask? In Manchester, for instance, there is the oft-repeated stereotype that Manchester City are the 'real' local team, while Manchester United attract support from further afield. Our map doesn't really support that idea though. There are only a few parts of Greater Manchester in which we see significant more tweets mentioning Manchester City than their local rivals. We also, strangely, see more mentions of Manchester City in Scotland and Merseyside, and more support for Manchester United in Northern Ireland.

The Merseyside rivalry (Liverpool vs. Everton) is another interesting one to map. There we see that Liverpool have the slight edge in the postcode that is home to both team's stadiums. However, there is no clear winner in the rest of the region: with most postcodes having a fairly close split between the two teams. Interestingly, many postcodes in Scotland seem to have more mentions of Everton; while many in Northern Ireland have more mentions of Liverpool.

We can also zoom into particular postcodes and see which teams are most mentioned there. The  academics in Oxford (for some strange reason) mention Manchester City more than any other team. Central Edinburgh (when not focusing on Hearts or Hibs) has more mentions of Everton than any other Club. And the Queen's home of SW1A goes for West Ham.

What about maybe the most important question of all. Who wins the league based on total number of Tweets sent from anywhere in the UK? The answer is Liverpool (a team that hasn't won the actual league since 1990).  Manchester United are a somewhat distant second, joined by Everton and Tottenham in the Champions League spots. We also find out that Fulham, Swansea, and Wigan are the three teams that get relegated due to their quite abysmal scores. Apparently just not that many people want to tweet about Wigan.

There is no doubt that using Tweets as a proxy for fandom is messy and not always reliable. In other words, we are mapping mentions and not measuring sentiment. But, the data do give us a rough sense of who is interested in (or at least talking about what), and where they are doing it from. It allows to begin to counter myths (e.g. that Mancunians don't support Manchester United), develop new insights about places that we don't necessarily have good data about, and most importantly, have some guesses as to which team the Queen might support.

See also:
A broader take on how information augments place (a second paper on the topic can be accessed here)
Other examples of our Twitter mapping (racism, flooding, earthquakes)
The code behind this visualisation (made freely [CC-BY-NC-SA] available on Github)