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Tag "Zuerich"

How does the social network link location as people communicate? It would be very interesting to see how communication pattern link to location and context.

There is already quite some good stuff on this topic. Only recently John Reads defended successfully his PhD on a topic in this field. He was looking at telecommunication patterns in the South East and London region base on land line connections. He found some interesting patterns of linkages and hubs and was able to identify regions according to dominant trades. Also some landscape features showed up. For example the Thames was acting as a barrier even in the realm of phone call connections.

The TwitterNetworks of London, San Francisco or Munich generated from the NCL datasets are quite interesting where we can see how individuals are connected via interaction on te Twitter plattform using @-tweets and RT-tweets. The networks are built establishing the edges using these two direction indicators. Other networks based on twitter data have been focusing on institutions and text as with the ‘Why Mediate Art‘ project.

Image by urbanTick for NCLn / Circular graph showing the connection between the data sets collected for different urban areas in Switzerland. No connections between them exist, each one operates separate.

Recently the NCL network ha been looking at areas in Switzerland and mapped out the four large urban areas Zuerich, Geneva, Basel and Bern. Overall it is quite visible that Twitter is not as popular as it is in other parts of the world. It is still sort of seen as a time waister and something for nerds. This was aso reflected in the language settings with foreign languages dominating the fields. It seems quite popular with people to keep in touch with other parts of the world.

Switzerland is quite small and the linkages between the cities are well established. This is supported by a perfect public transport network and a wealth of political mechanisms to ensure equality and exchange. However socially of course the different languages to separate different communities. French is spoken in the West, German in central and North and Italian in the South of Switzerland. In the middle of sorts there is the dominating geographical landscape feature, the alps acting as barriers.

This complicated setting of barriers and ties makes Switzerland an interesting study object for social networks. It would be great to see how the different urban areas connect via individuals on social networking platforms.

Regarding our Twitter data we have two data sources. One is the individual records for each urban area over the period of one week, the other is a week long record of location based tweets sent across the whole of Switzerland including the south of Germany and the north of Italy with Milan.

Image by urbanTick for NCLn / Showing the social connections as found on Twitter within Switzerland. Data based on a location based Twitter record over the period of one week.
The alps in the centre act as barrier with only a few connections crossing them, either via a celebrity Twitter account, in this case Justin Biber and Jessica Alba or physical travel.

Looking at the first data set with individual records for each urban area, the networks separate out each city with no established connections between them. It was sort of expected, since the sample is small and the parameters are tight with only location based tweets.

Looking at the second dataset where the whole area was simultaneously recorded the big barriers show up clearly and there is a well established separation between North and South showing the alps as mountainous Twitter blockers. Interesting however, are especially the links across this barrier and there are some. Three links connect the norther part consisting of Geneva, Basel, Bern, Zuerich and southern Germany with the southern part consisting of Milan, Como and Turin. They represent different types.

The first type is the link via a common third party that is not necessarily in the area. This is most likely a very active and popular twitter acount. In this case there are three celebrities that establish the connections. They are Justin Biber, Jessica Alba and some guy Kenny Hamilton. These are the hubs that individual Twitter users from both sides of the mountains tweet at and establish a sort of second grade connection.

There is also the other type of first hand connections. this is established by an individua traveling around and tweeting both to connections in Milan, the southern part and users in Zuerich, the northern part. The fact that the individual has actually physically traveled between the two parts enforces these connections.

Image by urbanTick for NCLn / Switzerland with the locations of recorded tweets. This has been collected over a period of one week. The purple line shows the route travels by one individual users tweeting along the way and interacting with other user from both sides of the mountainous barrier.

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Zuerich is the an important commercial centre for Switzerland. The city and the regio is home to a lot of international companies, a banking hub and as well as destination for a lot international celebrities or otherwise rich people to enjoying their wealth. With its international airport it maintains well establish international transport connections and let the location play a role in the European and international trade. For not being the political hub of Switzerland it is the busiest and largest agglomeration in the country.

It is however, in an international context a rather small hub with a population for the city and surrounding of just above 800’000 people. After a period of quite some decline of the urban quality in the late eighties and early nineties the city managed to turn these trends around and is since in a constant upwards trend. Zuerich featured for the past couple of years constantly in the top league of international city rankings, gaining points with the quality of urban spaces, ecology and sustainability. In the most recent Mercer 2010 list Zuerich features behind Vienna on the second place, just before Geneva, another Swiss city.

Zuerich New City Landscape
Image by urbanTick for NCL / Zuerich New City Landscape map generated from location based tweets collected over the period of one week. The area covered is within a 30 km radius of Zuerich.

The data for the Zuerich New City Landscape map has been collected earlier this year over the period of one week. In terms of its morphology the Zuerich landscape fits in with other cities showing independant island characteristics like Moscow or Sydney. The Zuerich New City Landscape (NCL) map is generated purely from geolocated tweets, sent over the period of one week using the devices GPS information. This is virtual landscape generated from tweet density sent from within a 30 km radius of Zuerich. NCL is an ongoing project, an world wide overwie of covered loactions can be accessed though HERE.

The ‘Bahnhofspitze’ above the main train statino is definitely the highest feature of the virtual landscape. It probably shows the importance of the city as a hub also for other regions of the country. With its relative proximity of the important cities there is a lot of commuting between the centres and Zuerich plays an important role, attracting a lt of workers on a daily basis from Basel and Bern as well as international. With the train network being extremely sophisticated and reliable it is the transport of choice for most of the traveling between the centres, hence the arrival or point of departure being the important feature.

Zuerich New City Landscape

Image by urbanTick using the GMap Image Cutter / Zuerich New City Landscape -Use the Google Maps style zoom function in the top right corner to zoom into the map and explore it in detail. Explore areas you know close up and find new locations you have never heard of. Click HERE for a full screen view. The maps were created using our CASA Tweet-O-Meter, in association with DigitalUrban and coded by Steven Gray, this New City Landscape represents location based twitter activity.

The timeRose over the twenty four hour period shows the twitter activities in Zuerich overall a mainly during the day. There is a fat mid day bit with people spending some on the platform. It looks as if people send in average only about one message around the lunch brake. Also now we feature data on platform used and language. Here the software of choice is the twitterfeed, followed by the twitter for iPhone app and the web. The twitter for Androids app only features at the very end of the top ten. It seems that Zuerich is a mac dominated market, at least for location based tweeting.

The international context is also supported by the fact that the English leads the table of the top ten used languages. German is only on second place. The top ten list also features Indonesian, Spanish, Dutch and French as group of languages used in the Zuerich area.

Image by urbanTick for NCL / The rose shows the twitter activity over the tweet activity per hour of the day, starting at 00:00 at the top. Here we are showing Zuerich local time. Hence the characteristic dip between three and five o’clock in the morning. Zuerich is a typical midday city with more activity around lunch time. The graphs show the platform of prefernce used to send the tweet and the language set respectively.

The data set is also animated in the aNCL series, coded by Anders Johansson and shows the whole set superimposed over the period of a twenty four hour period. The connecting lines indicate the dissemination of information between the individual users of the data set. Is a message retweeted by a fellow twitterer the visualisation draws a line with a traveling dot between the two location, starting at the initial senders position moving towards the position of retweeting by another twitter user.

Zuerich is in this context not very active at least it is not reflected in this data set. The previously animated San Francisco aNCL showed a lot more activity in this respect.

This animation is developed in collaboratively Anders Johansson and urbanTick. The data was collected using our CASA Tweet-O-Meter tool, coded by Steven Gray, in association with DigitalUrban.

There is more to come. We will be working our way through the NCL data collection of over 70 cities from around the world. Within the next week will be posting the next city to continue this aNCL (animated New City Landscape) series.

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