Last year Eric Fischer produced a great map (see below) visualising the language communities of Twitter. The map, perhaps unsurprisingly, closely matches the geographic extents of the world’s major linguistic groups. On seeing these broad patterns I wondered how well they applied to the international communities living in London. The graphic above shows the spatial distribution of about 470,000 geo-located tweets (collected and georeferenced by Steven Gray) grouped by the language stated in their user’s profile information*. Unsurprisingly, English is by far the most popular. More surprising, perhaps, is the very similar distributions of most of the other languages- with higher densities in central areas and a gradual spreading to the outskirts (I expected greater concentrations in particular areas of the city). Arabic (and Farsi) tweets are much more concentrated around the Hyde Park, Marble Arch and Edgware Road areas whilst the Russian tweeters tend to stick to the West End. Polish and Hungarian tweets appear the most evenly spread throughout London.

Even though the maps represent close to half a million tweets they are still based on a selective sample- they only include people who have a good location (either through GPS or a specific address) and those who are connected to the internet. I expect the latter requirement will exclude many short term visitors to London, and may explain why there aren’t so many hotspots around London’s landmarks (as is the case with Flickr where people can upload georeferenced images when they get home). In spite of this, I think the information in these maps is useful as a basis for comparison to other cities and it helps to reveal some of the finer patterns within the broad regions mapped by Fischer.

*this is slightly different to Eric Fischer’s method. He used Google’s translation tools to determine the language of each tweet whereas I have taken the stated language of each user because I am more interested in what users feel their preferred language is. I often see English tweeters post in French for example. Google also hasn’t quite mastered the slang or abbreviations that often crop up in Londoner’s tweets.

I think mapping Twitter’s engagement with the academic literature is important as it echos the map below and provides another example of the dominance of researchers (both in terms of access and production) from a few countries in the academic literature.

You can see how the “hotspots” of collaboration allign with the hotspots of tweets below.

One thing academics strive for is “impact”. This can mean many things, but one often applied criterion is the number of people outside of your immediate academic community that read your work. Twitter is becoming increasingly cited as an example of impact (for example how many followers an academic has), but as these maps demonstrate, much of the engaged audience is already where work is relatively easily accessible.

About the data from Altmetric:

“This dataset lists the ~ 58k tweets that mentioned a scientific article (broadly speaking anything with a DOI, PMID or arxiv ID) between the 1st and 31st of July 2011.

Recall isn’t 100%: my best estimate is that it’s missing another ~ 6k tweets where the article couldn’t be identified, the link was malformed or the journal involved is new or gets very low traffic.

Twitter’s TOS prohibit re-distribution of the tweets themselves but the dataset contains the extracted links, the tweet ID and some information about the tweeter (screen name, country & lat/lng derived from their location using Yahoo! Placemaker).“

It may not take off, or it could be come a weekly event. Either way you can monitor progress below or here.

I am therefore extremely impressed with the University of Waterloo’s (Canada)Snowtweets Project. The project, inspired by a UK snow map from Ben Marsh, encourages people to measure snow depths in their local area and instantly publish them to the web via Twitter. Snowtweet users can downlo

ad a standalone viewer called Snowbird that has been developed with Adobe Flex and Papervision3D.  The use of NASA Visible Earth Imagery, a clean interface and great graphics make this a very compelling application. I hope Snowtweets will become very popular in the Northern Hemisphere’s Winter so that it provides a great source of data by empowering the public to engage with cold/ temperate regions research.