Mapping #kony2012 on Twitter (part 2)

Following on from my last post about mapping #kony2012 on Twitter, I also wanted to offer up a map that shows the proportion of tweets from each country that made reference to the viral video or the LRA leader (or both).

We've already seen that most tweets referencing Kony were published from North America, and Western Europe, but this map tells a slightly different story. We now see that despite the very low total amount of content coming out of Sub-Saharan Africa (see the map below or read this post about where tweets come from), there is indeed a significant amount of focus on the Kony issue there.

But it remains that this is still a discussion that was largely taking place online in the Global North. While the top five countries in our sample (20% of all georeferenced tweets between March 5 and March 13, 2012) are: (1) USA; (2) Brasil; (3) Indonesia; (4) UK; (5) Mexico; and (6) Malaysia, the top five in terms of tweets that reference #kony are: (1)USA; (2) UK; (3) Canada; (4) Brasil; and (5) Ireland.

In other words, we see that while Twitter itself contains a lot of voices from the South, the discussion of Kony and Invisible Children remained firmly in the North.

***
Below I am also including a couple of maps showing the total number of tweets published during the same period:

Mapping Wikipedia edits from South America

If you've ever wondered where edits to Wikipedia come from in South America, the map below might be useful to you. 

The answer is that almost half of all edits to Wikipedia from South America come from Brazil. These data are actually not that surprising considering that there are almost 80 million Internet users in the country (and Brazil is home to about 45% of all of South America's connected population).

Chile is the country that scores a lot better than would be expected. The country is home to only about 5-6% of the continent's Internet population, but contributes over 12% of Wikipedia edits.

I've finally merged the Wikipedia data with Internet penetration data, so will be creating maps normalised by each country's connected population as soon as I get a few more free hours.

related:

Where do Wikipedia edits come from

Mapping edits to Wikipedia from the Middle East and North Africa

Mapping edits to Wikipedia from Africa

The geolinguistic contours of digital content in Spain

Following up on our post about augmented realities and uneven geographies, we wanted to post a few more maps that came out of the project.

This first one compares content indexed (by Google Maps) in Spanish (Castilian) to content in Catalan. Throughout much of the Catalonian region in the Northeast coastal areas there is considerable more content in Catalan than in Spanish.

The second compares content containing the word "love" in English and Spanish. The map reveals that while the Spanish term is much more predominant overall, there are clusters of locations along the Mediterranean coast at which there are more references to the English word.

These agglomerations are centered in tourism regions of Costa Brava, Costa Blanca, and the Andalusian coastline and closer inspection reveals that these concentration of hits are tied primarily to tourism related references to hotels, restaurants and other activities that are target to non-Spanish visitors.

One key thing that this map does then is reveal how the audiencing of augmentations can be alternately directed to a range of groups: ranging from the highly local (e.g. interpersonal relationships), to the global (e.g. tourist sites).

You can read more about the methods we used and our full conclusions in our new paper: "Augmented Realities and Uneven Geographies: Exploring the Geo-linguistic Contours of the Web."

O Mundo Pela Wikipédia

Some work done by Monica Stephens, Scott Hale and myself just got picked up by the Brazilian magazine Exame.

The spread offers an alternate visualisation to the data that we're collecting about the geographies of Wikipedia. It also includes penguins. I don't speak Portuguese, so am not sure what the penguins have to do with Wikipedia. But, being someone surrounded by virtual sheep, who am I to talk.

A PDF of the piece is here.

Jolie Holland - Catalpa Waltz (trying out Spotify's play button)

This is just a quick post to test out Spotify's new play button functionality. Spotify, more than any other online tool, file format, or technology, has fundamentally changed how I interact with music. Exploration and discovery become not just possible, but encouraged. And despite the fact that I used to both run an online radio station and work as a DJ at my college radio station, I'm pretty sure i've discovered more new (and brilliant) music in the last few years with Spotify's streaming service than at any other point in my life.

Anyway, if this play button gadget works well, I might try to share some playlists in the future.



(I've picked this track because I just discovered Jolie Holland's Catalpa a few days ago and haven't been able to stop listening to it since then)

Where do tweets come from? (part 2)

I realise that the graph in my last post about the geography of tweets is hard to read, so am uploading the chart below so that you can get a better sense of where content in Twitter comes from.  It shows us that over half of the world's content comes from the US and Brasil alone!

Again, all of the caveats of these data are listed in the earlier post.

Video of my DFID talk is now online: "Digital Divides - The Potential of the Internet for Development"

On March 29, I was invited by Michael Anderson to give a talk at DFID to extend some of the work that I presented at the London Cyberspace Conference last year. DFID have now uploaded my audio and slides and you can watch/listen to the talk below.

The idea behind the talk is that while it is important to not forget the revolutionary, and empowering promises and potentials of the Internet for the developing world, we also need to remember two extremely important caveats. First, despite a rapid growth in internet access for much of the world, most people on our planet are still entirely disconnected. Second, even amongst those two billion that are now online, a significant number are still left out of global networks, debates and conversations.

The Internet is a network that enables selective connections between people and information. And it is a network that is characterised by highly uneven geographies that have in many ways simply reinforced global patterns of visibility, representation and voice that we’re used to in the offline world. The issue isn’t just that some people in the developing world are disconnected, but also that many of the benefits of the Internet don’t automatically arrive into the developing world once Internet connections do.

So in other words, while the internet is clearly a pre-requisite for a lot of economic development and participation in the 21st century knowledge economy, we shouldn’t forget that it is by no means a determinant of any of those things.

You can also listen to (and see) the presentation in the slideshare below:

Digital Divides - The Potential of the Internet for Development

Where do tweets come from?

A couple of weeks ago, I posted a map of all georeferenced tweets mentioning the #kony video. The patterns were interesting, but not entirely unexpected.

A more interesting question though, would be to see what percentage of all tweets from each country reference #kony: in order to get a better sense of how focused people were on the event. However, to do that, we need to figure out how much content in Twitter actually comes from each country.

Devin Gaffney and I then collected all georeferenced tweets sent between March 5 and March 13 (it is important to point out that we are only dealing with a very small percentage of total tweets here [less than 1%], and so there may be significant geographic biases in where/how people georeference their content). We then took a random 20% sample of that dataset: giving us about 4.5 million tweets that we spatially joined to countries. The results are below:


(countries are on the x-axis)



The bar chart shows us the degree of inequality in where this content is coming from: with people in a few countries producing the bulk of content, and then a very long tail of countries from which very little content is produced.

Interestingly though, it is not just the usual suspects that are producing the bulk of content. The top six tweeters are:

(1) USA
(2) Brasil
(3) Indonesia
(4) UK
(5) Mexico
(6) Malaysia

Only two of the countries on that list are in the Global North and traditional hubs of the production of codified knowledge. What does this all tell us then? It is possible that Twitter is truly allowing for a 'democratisation' of information production and sharing because of its low barriers to entry and adaptability to mobile devices.

However, we need to do more work in this area to really figure out where content is coming from in the platform. Our sample in this post was limited, and more importantly we are still only dealing with georeferenced tweets that make up less than 1% of the total content that passes through the platform. An interesting start nonetheless.

(I'll post the Kony map normalised by number of tweets in each country soon)

Pictures from the Knowledge is Power symposium in Utrecht

The Dutch United Nations Student Association recently invited me to give the opening seminar in their 'Knowledge is Power' symposium in Utrecht. There were a variety of interesting lectures throughout the day, but - unfortunately for me - all but one were in Dutch.

The symposium was held in the beautiful Jacobikerk, and I'm uploading a few photos of the event. Mostly because I've never given a lecture in a church before.

Thanks to the organisers for a very enjoyable and stimulating trip.

Interactive Wikipedia mapping tool

We know by now that all online platforms have distinct, and highly uneven, geographies. Wikipedia is no exception: and we therefore decided to make a tool that would allow people to explore what, and where, the world's most popular encyclopedia represents. 

The tool, made by the excellent team at TraceMedia, as well as the Oxford Internet Institute's Bernie Hogan, and myself (Mark Graham) can be accessed at the following link. 

The tool is built as part of our project to study participation and representation on Wikipedia in the Middle East and North Africa. It currently allows you to explore the geography of all geotagged Wikipedia articles in Arabic, Egyptian Arabic, English, Farsi, French, Hebrew and Swahili. It also allows mapping of a range of metrics including the word count of an article, date created, number of authors, and number of images. 

A few screenshots of the tool are below. You can also read more about how it was built, or simply start playing. The tool is still work in progress, and there is a lot to add and fix, but we hope it is useful in the meantime!