4/10 Why Mediate Art? - Twitter Text Network

Milan based Mousse magazine is running a series with the title 'Ten Fundamental Questions of Curating'. The editor of the series, Jens Hoffmann explains: "it emerged from a desire to trace the coordinates of contemporary curatorial practice, to take stock of a profession that is constantly evolving. Through the contributions of ten curators, the ten essays in the project examine ten fundamental themes in curating. The booklets are structured as hypothetical chapters in a book that once completed, through the reflections of some of the leading figures in the contemporary scene, will try to offer an answer to the question of “what it means to be a curator today”

I was invited by the London based artist Marysia Lewandowska to collaborate on her contribution to the fourth edition.


Image taken from Mousse / Page one of '4/10 Why Mediate Art?'.

The fourth instalment of “Ten Fundamental Questions of Curating” looks for an answer to the question “Why Mediate Art?”. The editor Jens Hoffmann invited Maria Lind to contribute who in turn proposed to work with Marysia Lewandowska as an artist curator collaboration. In her text Maria Lind examines the seeming paradoxes that revolve around art institutions: an overabundance of traditional educational activities, aimed at engaging an ever broader public; marketing departments and press offices that take on a strategic role; curators who have no real interest in making their project known outside the professional sphere. The Swedish curator explains the importance of weaving connections between works, curatorial projects and the public, for a new kind of artistic “mediation”. Marysia Lewandowska proposal extends the meaning of mediation in our networked culture by connecting the ‘followers’ of major contemporary art museum and public galleries and Maria Lind’s text through twitter.


Image taken from Mousse / Page one of '4/10 Why Mediate Art?'. Click Image for the interactive version.

This is the time when art is mediated to its audience not only through lectures, seminars, artists’ talks, guided tours and publications but when mediation intervenes as a pulsating stream of immediacy, mixing the promotional intentions of the institution with the visitors’ desires of sharing their observations and responses. The banal is closely entangled with the political, the randomness is attached to a system as announced by the ubiquitous banner: Twitter is a rich source of instantly updated information. It's easy to stay updated on an incredibly wide variety of topics. By utilising the social networking platforms such as Facebook, YouTube and Twitter that emerged over the past few years, the communication between the art institutions and their audiences has grown into a real time stream of information snippets.

Interactive version created by single-blogs using the GMap Image Cutter / Twitter Education. Tweets collected using 140kit, to visualise the network Gephi was used. Click HERE for the full screen version.

What appears on the visuals are graphs mapping tweets sent by three major art institutions, Tate in London, MOMA in New York and Moderna Museet in Stockholm to communicate and mediate their activities as they are enmeshed together with Maria Lind’s text. The two text streams have been aggregated as a word chain, where each word is connected with a link to the following word in the sentence. Each word is represented only once as a node in the chain, but in many cases with multiple connections, edges, to the following words. The resulting visualisation is of a network based on the structure of the words in use. The two different sources are distinguished where red lines represent the links between the words in the tweets sent by the art institutions, while the black lines show the flow of the essay written by Maria Lind. The tweets cover the period between 2009-09-16,15:18 and 2010-11-29 16:03.


Image taken from Mousse / Page one of '4/10 Why Mediate Art?'. Tweets collected using 140kit, to visualise the network Gephi was used. Click Image for the interactive version.

For artist Marysia Lewandowska the mapping of this flow expresses a desire and interest in distributive networks without restriction; it is the desire of being in touch and engaged, of organising one’s thoughts and sharing them instantly. The knowledge ecologies of a wider world intersect in unexpected ways and point to the role mediation plays in shaping our current social and political life.

Publication - Mousse, Editor - Jens Hoffmann, Text – Maria Lind, Art – Marysia Lewandowska, published 2011.

Ten Fundamental Questions of Curating, edited by Jens Hoffmann and published by Mousse in collaboration with the Fiorucci Art Trust, is distributed with the international edition of Mousse and with subscription copies.

Interactive version created by single-blogs using the GMap Image Cutter / Twitter Education. Tweets collected using 140kit, to visualise the network Gephi was used. Click HERE for the full screen version.

Twitter Ecosystem

Not quite sure which app to use to read and write your tweets? Well it is tricky and there are loads of options out there. Actually it has become a whole Twitter Ecosystem with apps growing into from everywhere, all aiming for the best place under the twitter sun.

Brian Solis and JESS3 created a visual depiction of the, what they call, Twitterverse (as in universe actually). The graphics shows loads of twitter apps neatly ordered and lined up on concentric rings of types. These range form Geographics like trendsmap to rich media like yFrog, to mobile apps like echofone, to twitter search like twazzup.

Each group has its speciality and a niche. This works quite nicely for users. However there is also some overlap between some and this is where it rumbles in the ecosystem.

Check out the interactive map, you can click on the names for in-depth info about each service. Feel free to order the poster-sized infographic to hang in your office and teach others about Twitter, or download the image map for your blog. Via Flowtown.


Map by Brian Solis and JESS3 / A visual depiction of the Twitter ecosystem, the Twitterverse, to help you learn more about all the tools available. Click the image for the interactive version.

Social Interaction on Time

Getting the tweets out on time, actually at the right time, is very easy since the invention of Timely the on time tweet tool discussed earlier in 'Social Networking on Time'. Now the tool has been refreshed.

Timely allows to schedule a whole list of twitter messages and sends them out at the best time optimizing reader outreach. Based on the past 200 tweets a timeframe for best outreach is calculated and following tweets are sent out at exactly the best time.

The tool developed by the flowtown team just got better, with a major update released today. 'Timely Gets An Activity Stream' with stats that are actually transparent and reliable. It is still the basic number, but there is now a drop down menue showing the actual retweets. Each tweet is listed chronologically just like in the Twitter stream. This streamlines the task of finding out who retweeted and in which context. No need to run a search through Twitter, Timely delivers it straight to the dashboard.


Image by single-blogs taken from Timely / single-blogs on Timely with the update listing function of retweets.

Further, it is possible to take it a step further and replay directly to each retweet. It offers basic function of an @tweet. This means thanks and ad-dons can be sent from the same platform. With this the information delivery and management goes in one and the from the ground up rebuilt Performance service gives every ambitious promoter peace of mind out of the box.

As Jason Keath from socialFresh points out: Timely has been open to the public since February, and already needs to expand the capability of their service to account for increased use. The service currently has over 15,000 total accounts and continues to grow.


Image by single-blogs taken from Timely / Timely now allows to directly replay to Twitter users who retweeted timed tweets served through Timely.

New City Landscape - Seoul

Seoul is the capital and largest city of South Korea. A megacity with a population of over 10 million, it is one of the largest cities in the world. Seoul proper is noted for its population density, which is almost twice as concentrated as New York and eight times greater than Rome, though slightly less than that of Paris. The use of technology in everyday live is very integrated, even more so than in western cities that only are discovering the connectedness. In this sense the number of tweets being sent from Seoul is very high, with a high percentage of location based tweets.

The Seoul 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 the Seoul region. NCL is an ongoing project and we have covered cities worldwide. An overview can be found HERE.


Image by single-blogs for NCL / Seoul 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 Seoul.

In terms of the morphology, the Seoul NCL is a type with more than one centre. There are two main centres with additional smaller centres of high activity. Even though it is not visible, the river dividing the two main centres can be imagined from the landscape. The smaller centres dotted around belong to 'new towns' built around 1980 with predominately residential usage.

The main area to the West is the 'old centre' of Seoul with the formal institutions, the palace and the main tourist destinations. There is also business, mainly baking and shopping. The main area to the East is the 'new centre' with a sort of London Soho touch. This includes again shopping and business.

Regarding the airport, wich is usually a very active spot on the NCL maps, in Soul the International airport is outside the covered area, but the old Seoul airport for domestic flights is on there to the West of the centre. However, it is not very active and only shows as a small hill.

Seoul New City Landscape

Image by single-blogs using the GMap Image Cutter / Seoul 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. Thanks for the help with the labeling to Sung-Hyun Jang from AR+GIS.

The temporal usage of twitter in Seoul is indeed different from the European and American cities. There is on the week day rose a clear preference for mid week activity. The weekend is not very active also Monday is very slow. On the 24 hours scale Seoul shows the typical dip in the early morning hours around 3-4 o'clock, but other than that it does not relate to the kidney shape of western cities. It has some four peaks, one in the morning one over midday, one in the evening and one around midnight. It look as if people in Seoul would tweet more or less four times a day. Overall it is one of the cities more active in the second part of the day with a very late night.


Image by single-blogs for NCL / The lefthand rose shows the twitter activity over the days of the week, starting with Sunday at the top, going clockwise. The rose on the right shows the tweet activity per hour of the day, starting at 00:00 at the top. Here we are showing local time in Seoul. Hence the characteristic dip between three and five o'clock in the morning. Seoul is a typical evening city with more activity n the late hours of the day. For more details on the time comparision with other NCL urban areas please see the presentation post 'Twitter Data - Seeking Spatial Patter'

NCL San Francisco - Update

Following the SFO aNCL, an update to the earlier San Francisco map was needed. The slight redesign of the map islands with changed key and added graphs of temporal elements. The exclusive islandification of the area is enforce with a new frame. This provides more visual stability, allowing for stronger vertical orientation.



Regarding the temporal elements, San Francisco is an evening city. The lefthand rose shows the twitter activity over the days of the week, starting with Sunday at the top, going clockwise. The rose on the right shows the tweet activity per hour of the day, starting at 00:00 at the top. Here we are showing local time in San Francisco. Hence the characteristic dip between three and five o'clock in the morning. San Francisco is a typical evening city with more activity in the late hours of the day. There is a lot more activity in the later hours of the day than there is in the mornings. Comparing to Bogotá for example, a morning city, SFO has this lag with a first peak around noon and then high activity between 20h00 and 23h00. After that it drops off quite quickly, being considerably lower around midnight reaching the base around 3 am.



San Francisco New City Landscape



Image by single-blogs using the GMap Image Cutter / San Francisco 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.

San Francisco is Busy - aNCL Series

San Francisco is busy tweeting and this new animation of location based tweets in the Bay Area show actually how busy it is. Geo located tweets are shown as yellow circles that fade away by time, and re-tweets are shown as small yellow points moving onto a line connecting the location of the original tweet and the geo location of the re-tweeter.

The data used is the same as for the San Francisco New City Landscape (NCL) map. Where a virtual landscape was generated from the tweets. More details HERE. This new animated version shows in detail how the different centres ebb and flow as time passes. There are distinct characteristics between the location over times of the day. Basically the Bay bridge keeps it all together.

Interestingly the RT's are a very specific day thing. During the night this information channel is not ver active and people seem to be busy tweeting their own stuff. In a sense this could be hinting at a more formal and business use of the RT function.

This animation is developed in collaboratively Anders Johansson and single-blogs. 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.

MTV Music Awards 2010 - Visualisation

THe MTV Music Awards are one of the really big yearly music shows and as such a important date in the calendar. Of course this transfers to the social networking sites, with loads of followers chatting about it online.

For last years show Stamen has teamed up with MTV and Twitter to deliver a live visualisation of the conversations on twitter about the stars related to the show. The whole thing was based on word tags, counts to indicated how often each star was mentioned. These numbers feed into the visualisation showing an icon for each performer in the relative size of its online counter.


Image taken from fastcompany / screen shot of the live visualisation created by Stamen for the MTV Music Awards 2010.

This generates this bubble size chart layout, with the higher rated names moving into the centre. There is obviously some direct action going on between the fn camps of the individual stars and the online conversations reflect pretty much in real time the activity on screen. People are tweeting as they watch, mainly in front of the tv, presumably. As Stamen points out:"Midway through the video, Taylor Swift gets up on stage to receive her first Video Music Award—to have it promptly snatched from her grasp by Kanye West, who immediately blows up on Twitter."

NCL Bogotá - the Cut

The Columbian capital is quite an active spot with tweeters. In general the twitter platform is very popular in South America and Bogota is no exemption. However it is in terms of overall numbers behind fanatic tweeters such as Sao Paulo and Rio, but in Bogota we still have quite a good number of location based tweets. There are about 18% of the tweets geolocated providing a good base for the Bogota New City Landscape Map (NCL).

The NCL map is generated as a virtual landscape from geolocated tweets sent from within a 30 km radius of the Bogota area over the period of one week. NCL is an ongoing project and we have covered earlier that can be found through HERE.

The striking thing is the extreme cluster tendency in this version of the map. The twitter activity is simply and only concentrated in the business area of the capital along Carrera 7. No wonder this is where things are happening with a lineup of business, shopping and nightlife, where else would you go. This must also be where the money is, since the sample does require the users to use one of the more recent mobile gadgets. Hence the large void to the south and west, where lesser people are using the service. The third large void is defined by the large mountain ridge Cerros Orientales. The landscape feature her as a cut, both on the virtual scape and in the real world.


Image by single-blogs for NCL / Bogotá 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 Bogotá.

In terms of the morphology, even though Bogota NCL features a singular hotspot like the lot of London, Paris, Barcelona it fits more with the feature structure of New York or San Francisco. Especially in term sof how it relate to the physical structure of the city fitting in along this mountain ridge, witch is sort of 1 to 1 reflected in the virtual twitter landscape.

The detailed overview of NCL cities from around the world can be found on the NCL World View, with links to the individual interactive versions.

Bogotá New City Landscape

Image by single-blogs using the GMap Image Cutter / Bogotá 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. Thanks for the help with the labeling to Luis Suarez from EstudioArQ.


Image by single-blogs for NCL / The lefthand rose shows the twitter activity over the days of the week, starting with Sunday at the top, going clockwise. The rose on the right shows the tweet activity per hour of the day, starting at 00:00 at the top. Here we are showing local time in Bogota. Hence the characteristic dip between three and five o'clock in the morning. Bogota is a typical morning city with more activity n the morning hours of the day. For more details on the time comparision with other NCL urban areas please see the presentation post 'Twitter Data - Seeking Spatial Patter'

Visualisation in the Age of Computerisation - Conference

The Institute for Science, Innovation and Society (InSIS) is organising a two-day conference 'Visualisation in the Age of Computerisation' on 25-26 March 2011 at Saïd Business School, University of Oxford.
"The theme of the conference is the permeation of science and research with computational seeing. How does computer mediated vision as a mode of engagement with information as well as with one another effect what we see (or think we see), and what we take ourselves to know?"

The event is structured along three main topics: Changing Notions of Cognition, Changing Notions of Objectivity and Changing ontologies of scientific vision.


Image taken from onlinejournalism blog / for a viral-friendly piece of visualisation, it’s hard to beat this image of festival rainfall in the past 3 decades.

Speakers include: Peter Galison, Department of the History of Science, Harvard University, Michael Lynch, Department of Science and Technology Studies, Cornell University, Steve Woolgar, InSIS, Saïd Business School, University of Oxford and the summarising discussants are: Anne Beaulieu, Virtual Knowledge Studio, Paolo Quattrone, IE Business School and Fulbright New Century Scholar

I will be presenting a paper together with Tim Webmoore on ethics and visualisation of large scale dataset mined from the web, with a focus on twitter. We'll be using the NCL mapping project for examples, to develop an illustrated argument for ethics in this field. However, the aim is to use ethics to support this kind of research, using ethics and a clear position as a framework. We believe that such structures are of additional value to the research and researchers and ensure in the long term academic research quality and standards.

Abstract: In this paper, we examine some of the implications of born-digital research environments by discussing the emergence of data mining and analysis of social media platforms. With the rise of individual online activity in chat rooms, social networking platforms and now micro-blogging services new repositories for social science research have become available in large quantities. The change in sample sizes, for instances, from 100 participants to 100,000 is a dramatic challenge in numerous ways, technically, politically, but also in terms of ethics and visualisation. Given the changes of scale that accompany such research, both in terms of data mining and communication of results, we term this type of research 'massified research'. These challenges circle around how the scale of, and coordination work involved with, this digitally enabled research enacts different researcher-participant relationships. Consequently, much of the very innovative and creative research resulting from mining such open data sets operates on the boundaries of institutional guidelines for accountability. In this paper we argue that while the private and commercial processing of these new massive datasets is far from unproblematic, the use by academic practitioners poses particular challenges. These challenges are manifold by the augmentation of the capacity to distribute and access the results of such research, particularly in the form of web-based visualisations.
Specifically we are looking at the spatial and temporal implications of raw data and processed data. We consider the case study of using Twitter's public API or application programming interface for research and visualisation. An important spatial consequence of such born-digital research is the embedding of geo-locative technology into many of these platforms. A temporal consequence has to do with the creation of 'digital heritage', or the archiving of online traces that would otherwise be erased. To unpack these implications we consider how a selection of tweets can be collected and turned into data sets amenable to content and spatial analysis. Finally, we step through how visualisation transforms such vast quantities of tabular data into a more comprehensible format through the presentation of several visualisations generated from Twitter's API. These include what one of us has developed as 'Tweetographies' of urban landscapes, as well as examples of recent Twitter activity surrounding the disasters in Japan.
Such analysis raises issues of privacy and ethics in relation to academic ethical approval committees' standards of informed consent and risk reduction to participants. Such massified research and its outputs operate in a grey area of undefined conduct with respect to these concerns. For instance, what are the shifting boundaries of public and private space when using Twitter and other platforms like it? Are Twitter and other social media platforms' disclaimers as to privacy sufficient justification for academic and commercial use? Are the standards of social science research protocols applicable to research on and for 'the masses'?
To conclude, we discuss propose some potential best practices or protocols to extend current procedures and guidelines for such massified research.


Image taken from Nora Oberle's blog / Another beautiful data visualisation. Even though in this case, the topic is not that hilarious- it’s about news coverage of scare stories. Remember tumours and cellphones or “killer wifi”?

Full conference programm to download HERE.

Twitter Wave in Honolulu

The tsunami wave, generated by the 9.0 magnitude earthquake of the East coast of Japan on the 11 March 2011, spread through out the pacific threatening many coastal sections in different countries. The water fore strongest hit the Japanese coast shortly after the earthquake. All other countries had a little more time to evacuate and prepare. Hawaii, was one of the next destinations in the line of the wave. The arrival was expected by NOAA, the tsunami warning centre, around 13h17 the same day.

Looking at the activity on twitter during the tsunami we are on the search for clues about the relationship between twitter and an unfolding natural disaster. As an inspiration to serves the XKCD PhD comic 'Seismic Waves'.

In this close look at twitter activity related to the tsunami resulting from the earthquake, Anders Johanson has animated the messages for one hour before and one hour after the expected arrival time of the tsunami wave in Honolulu on Hawaii. The messages are collected through the usual NCL collection method and are focusing on actual geo located tweets that contain lat/long information. Johanson explains "At the time instant when each new tweet is posted, a bright red blob appears on the map, and this blob is then decaying in intensity and size. Re-tweets are shown as an arrow, pointing from the original source of information. Interestingly enough, the information wave has the same direction as the seismic wave. However, there are obviously way too few data points to enable a rigorous spatio-temporal analysis in this case."


IMage by single-blogs for NCL / The graph shows the number of geo located tweets sent per hour from Honolulu, on 2011-03-11, in a radius of 30 km on the day the tsunami resulting from the earlier earthquake in Japan was expected to reach the Hawaiian coast. In white are the overal tweets and in purple the tweets containing the key words wave, tsunami and earthquake or Japan. The first dotted line from the left is the expected arrival time of the wave on the coast of Hawaii at around 13h07 UTC. The second dotted line is the arrival time of the wave on the coast of Mexico.

The tsunami arrived in Hawaii and hit hard, causing damages estimated to be in the tens of millions of dollars. On the twitter scape on the other hand, there is a slight increase of activity after the wave, but actually very little. However, as you can note in the graph above there are more tweets using the keywords related to the natural disaster unfolding than there are thereafter, especially after the wave arrived in Mexico.




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UPDATE 2011-03-18
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Processing the twitter data some further, the spikes on the keywords do fade out nicely in the hours afterwards. This time we are working with the larger data set containing all the located tweets including the geo located tweets. This data set differs from the one used earlier as that it included reverse geocoded locations, eg places, but not necessarily pure lat/long messages. This set contains some 260'000 messages as compared to some 20'000 geo located in the earlier dataset.

Looking at the event over longer period shows the pattern much clearer. There is a lot more activity around the expected tsunami wave and the dying out of the keywords can be observed in the following hours and days. However it also confirms that to some extend the purely geo located tweets, as a sub set, folow largely the same pattern and are not

Note, there is a baseline tweet containing the term 'wave' that we picked up as part of the collection. This is a weather boy just of Honolulu tweeting the current status of the water, wave and wind.


Image by single-blogs for NCL / The graph shows the number of geo located tweets sent per hour from Honolulu after 2011-03-11, in a radius of 30 km on the day the tsunami resulting from the earlier earthquake in Japan was expected to reach the Hawaiian coast. In white are the overal tweets and in purple the tweets containing the key words wave, tsunami, earthquake or Japan. The first dotted line from the left is the expected arrival time of the wave on the coast of Hawaii at around 13h07 UTC. The second dotted line is the arrival time of the wave on the coast of Mexico.

Twitter Data - Seeking Spatial Pattern

I will be contributing to the CASA seminar tonight, given by Robin Morphet, Steven Gray and myself. It will be an update on the NCL - New City Landscape data collected from twitter. The collection of monitored urban areas around the world has now grown to over 60 location.

The update focuses on three elements, data pool, temporal activities of cities overal, and networks within the cities. There are also some additional aspects, for examples a view of the first three weeks of the revolution in Egypt as documented earlier focusing on Cairo.


Image by single-blogs / Tweet activity in Cairo around the Tahrir Square in the centre of the city and at the heart of the revolution. This is using Cartographic for the mapping of the data with a bing map in the background.

The temporal aspects show variations between the different cities. As a mode of classification a sample of nine cities have been ordered from evening to morning. Some cities seem to be more active in the morning and other in the evening. Dubai and Istanbul for example are clearly more active in the late hours, where on the other end Cairo and Bogota are early birds and tweet a lot more in the morning. The US cities Boston and Atlanta have both a peak in the morning and in the evening.


Image by single-blogs for NCL / timeRose diagram of 24 hours - showing twitter activity in percentage of total tweets by hour of the day. Covers the cities Cairo, Bogota, Mexico City, Manila, Atlanta ,Boston Los Angeles, Istanbul, Dubai.

Similarly there are preferences regarding the weekdays. Not all areas tweet the same day. The early week days, Monday and Tuesday are generally less active than the rest of the week. Manila clearly prefers the weekend, where Cairo, Istanbul and Mexico City prefer the end of the week, Thursday and Friday. Dubai and especially Bogota have the least differences between the weekdays with very similar numbers of tweets through out the week.


Image by single-blogs for NCL / timeRose diagram of the weekdays - showing twitter activity in percentage of total tweets sent by day of the week. Covers the cities Cairo, Bogota, Mexico City, Manila, Atlanta ,Boston Los Angeles, Istanbul, Dubai.

As a preview below you find the slides for the talk tonight. Some of the stuff has featured earlier on the blog. So you will ind some background there. You might try the tweetography tag or the twitter tag to dig down. It might involve a bit of scrolling to get to the earlier posts. Anyway if you have time come along tonight for the live update.

Social Networking on Time

The thing with time is that if your not on it, you might have missed it. The opportunity windows are small and meeting with others' shedule might be tricky. This is the same in the ever so present online networking world. Nothing is more boring than a static profile page as you might have on linkedIn or Academia. However, this is one of the option for not to get missed, just be always there.

In the ephemeral world of twitter, facebook, gowalla or foursquare this is not an option. If your facebook page hasn't changed in the past day, something is wrong, if you haven't checked in at any location that day on foursquare you must be very ill and in bed and if you did not send any tweets in the past hour this isn't gona work.


Image taken from tech cocktail / timely logo.

The flow of tweets however, does not guarantee that if you tweet your tweet is being read. On the contrary things are changing fast and as a tweeter your basically battling on your own against the rest of the tweeter kingdom for a sunny spot on the top of any readers list, but on time. Right at that moment this follower of yours is actually reading the first three tweets on the feed, picks the one you wrote and retweets or replays or clicks, but does something with it.

This is tricky, but time is on our side, or better the human desire to organise around it in cycles. Even here on tweet-eden routine rules the behaviour and there is a certain time of the day your tweets will have the prime spot, most-impact-in-24-hours-moment it would be called.

And of course there is an app for everything - here is TIMELY. It is simple but functional. Write a tweet you want to send out, timely looks through your past 199 re-tweeted tweets checks them agains a 24 hour timeframe and calculates the time of the day your tweets had the most impact in the past. At this very moment in the upcoming 24 hours your tweet will be sent. Ever though of something like that?

There isn't much more to it, really. And to proof the point, the guys at timely, actually flowtown, provide you a basic statistic with the past tweets send on this platform showing the number of clicks, the number of retweets and the number of readers (potential readers) your tweet has had so far.

With this you can really start to enjoy your day. No more worries about keeping up with the bomb shell tweet, just follow the stream of incoming messages, relaxed you can watch other struggle along with tweeting, everything with the peace of mind that your three tweets scheduled will be on time. Thats all that counts.


Image taken from single-blogs on flickr / Screenshot of my timely performance panel.

Of course timely does offer other functions, for example you can have multiple accounts, or invite other people to schedule tweets on your timeline, this is great for collaboration on one account. It features an integrated url shortener that actually work The settings allow you to controle how many tweets will be sent per 24 hours and accordingly the analysis will be adjusted. Weekends can be different or ignored and you can also force a tweet to go out in the next 30 minutes, of course timed to fit the best time frame.

One thing to mention though is that the management of the queue, you can prewrite a whole list of tweets, is tricky since there is only a delete, edit or move to the top button. A move up and down, especially for the top few in the queue would be very handy.

Anyway try it for yourself and get your tweets out on time. At least some of them, you can still use in parallel other platforms to reply or interact, this is gona be the back bone to keep your twitter account running on time!

Twitter Usage - A View on America

More and more studies start to reveil the anatomy of twitter usage. So far it was more guess work as to who is actualy using the social-network-microblogging-news-share-shout platform. Earlier the Twitter Fact sheet gave some information on the general usage overall. This earlier research was focusing on twitter's performance and service. What it didn't unveil was the internal structure, who is using it and what they are using it for.

A recent study by the Pew Research Centre has now put together data on twitter usage in America. They have now focused on users and the study has some interesting results. Here are three key findings:
Young adults – Internet users ages 18-29 are significantly more likely to use Twitter than older adults.

African-Americans and Latinos – Minority internet users are more than twice as likely to use Twitter as are white internet users.
Urbanites – Urban residents are roughly twice as likely to use Twitter as rural dwellers.
The age divide and the urban rural divide was expected, more details below, but the ethnicity variations are rather surprising.

The data was collected in October and November 2010 and is therefore very recent. However the twitter landscape changes rapidly and this data soon needs to be reevaluated. For a detailed description on the methodology to collect the data have a read HERE.

In addition to the above three key points a few additional facts stand out. Women (10%) are using the service more actively than men (7%). It is a cliche, but woman are better at multitasking and this is what twitter requires. An active user has to be able to switch between current activity, twitter usage such as catching up with the feed, replay or link and then switch back.

In terms of how often a user checks the feed the categories are drawn very broad. It comes in seven categories of which only two are focusing on the day as a unit, several times a day (24%) and once a day (12%). The other categories are every 1-2 days (12%), every 3-5 days (5%), every few weeks (7%), less often (20%) and never. The never categorie is with 21% about the same as the several times a day with 24% and is of course an important category. However the nature of the twitter service is real time and messages are in the constant flow ephemeral in terms of duration and validity. In this sense categories such as once every 3-5 days don't make any sense. Instead categories should be smaller capturing peoples adictedness during the day. Everything beyond two days could have been less often and therefore having categories several times per hour, every hour, 1-2 hours, every quarter of a day, twice a day.

Another section of the study looks at the content users actually post. Here the personal stuff (72%) dominates closely followed by work stuff (62%). Probably the work related content was not expected to be this high. It shows that twitter has definitely become a valuable business tool for both distributing and receiving information as well as mingin and getting a feel for trends.
55% are posting news, 54% post "humorous or philosophical observations about life in general", jokes basically. So very close together thee two categories. This is the same for interaction, as retweets (53%) and messages (52%) are very similar. In terms of additional content 40% share a photo, 28% share a video and only 24% share their location. For photos and videos one can suspect that these categories are just simple to track, but might not be valid.

And lastly, the educational and financial background of the twitter users in this data set. Better educated means your more likely to tweet, but only by a few percent. In terms of income it is interesting that low and high incomes tweet more than middle and very high income. However, this observation corresponds directly with some of the observations we have made in the New City Landscape tweetography maps, especially the London map. Having now these numbers could help interpret these result in more detail.

Some comments on how the study is constructed and what aspects were looked at can be made along the above aspects measured. Similar to the units used to look at the activity in term of time, it almost seems as if who ever set up the framework for this study did not understand how twitter works. The categories are too broad and not specific enough. The temporal aspect was discussed earlier, but also the content of the messages would need to be assessed in more detail. Private and work are broad fields and what can be assumed with these new medias is that them two start to blur quite easily and quickly. This would require specific attention. Further more the fact that all the numbers are simply given a percentage of internet users does not live u to the fact that twitter actually is something new and no longer 'internet based' in the classical sense. The study is based on the assumption that all the twitter users are aso interne users, eg access twitter through the website. A lot of twitter users access twitter through a third party client, this could basically be any platform. There is of course also a large group using mobile or smart phones to send or read tweets. This is not in the conventional sense to be classified as internet usage. This is quite unique and new with these services, which would include Gowalla, Foursquare, Stickybits and so on, that they operate through different and new channels.

Here is a graph taken from Flowtown, visualising all the results discussed above. However I am not sure about the gender as well as the education graph, the original data from Pew shows different numbers, the ons used in the description above.


Image taken from Flowtown - Social Media Marketing Application / A visualisation of the study results collected by the Pew Research Centre and put together by Flowtown.

Via Flowtown

Invisible Cities - Web 2.0 for the Desktop

Visualising virtual activity location based and linking it visually to the urban locations it takes place is one of the ideas of New City Landscape (NCL). Using the twitter feed the location based tweets are aggregated and the density is mapped as a virtual landscape. This landscape's features are named after the corresponding real world places, creating a sense of place and orientation.

However, so far the NCL maps have been static and in retrospect, representing a week worth of data about the specific urban area they portrait.

Around the same time Christian Marc Schmidt has developed a similar approach focusing on Manhattan, but visualising in real time twitter and flickr activity. The density landscape here is mapped using the aerial photos morphing it over rising and falling peaks. He takes the aspect of real time into account and focuses the visualisation on what is happening just now.


Image taken from Invisible City / Aerial view of a topic path with the earliest record selected.

The project has now developed in to a standalone desktop version that can be played around with locally. It connects to twitter and flickr loading the most recent activity of the past 24 hours. The applet is Java based and runs on Mac and Windows.

The landscape is based on the activity, each message or photo is shown as a white dot. Hovering over dots reveals the message and details, plus draws links to previous or following messages. These paths are generated from topics listed on te right hand side of the window. If a node belongs to a topic path, navigation will also appear at the top of the view with previous/next buttons to move chronologically along the path.

Schmidt explains: "Invisible Cities, a project named after the novel by Italo Calvino, aims to provide insight into the composition of urban social networks by surfacing data from online services, geographically mapped, in order to identify the areas of high and low activity. The visualization thus reveals emerging social themes, presented in a three-dimensional spatial environment. It displays individual Twitter status updates and Flickr photos on a geo-registered surface reflecting aggregate activity over time. As data records are accrued, the surface transforms into hills and valleys representing areas with high and low densities of data. Data points are connected in chronological order by paths representing themes extracted from status updates and image metadata."


Image taken from Invisible City / A selected photo as part of a two-node topic path.

You can download the Java App for MacOSx or Windows. A detailed description pdf can be read HERE and the project website with more screnshots and clips can be found HERE.

Egypt is Back on the Net and Twitter Activity Surges

Following the previous post on location based tweets in Cairo during the government imposed internet black out some new Twitter data is now showing that there was a clear reduction in tweets.
The forced black out halted most internet activity during the last week of January and the first days of February. Finally on Feruary 2nd between 09h30 and 10h00 Egypt was reconnected acording to data colected by Renesys.

24 hours after the switch was turned back on the data shows an immediate raise of geolocated tweets. The activity came back up from a down of around 50 tweets per hour to 230 per hour.


Graph by single-blogs / Tweets collected using the TOM tool written by Steven Gray. The tool collects geolocated tweets originating within a 30km radius around the centre of Cairo. The graph shows number of tweets sent per hour.

This graph now shows a lo better what was going on. With the surge where tweets kick back in, the reductions is put into context and maks sense. However why there is still relatively many tweets during the black out is more difficult to explain. It is assumed that low quality channels were available but with very long delays putting more and more people of, hence the slow reduction.

Egypt's Internet Blockage - Tweets

The news that Egypt has gone of the internet last Thursday night, stunned the internet community. The news swooshed around quickly and questions were asked. How is this possible, is there a switch?

Over the past years we have learned to appreciate the net as a distributed network of hubs and servers with its own rules. Those being that the internet is not centrally managed and therefore very difficult to govern, even navigate. However, the net of nets is still connected via physical routers, as Andrew Blum in post over at the Atlantic points out.

The move by the Egyptian government was intended to help regain controle over the masses of people who protested for change on the streets of the major cities. The government seemed to believe that the internet and especially social media platforms such as Facebook a and Twitter are increasingly playing a role in the organisation of protests. Cutting Egypt off the web would leave the protesters unable to organise themselves.

Shortly after midnight, about 22h00 UTS, the Egyptian internet providers were asked to take down their routers. One after the other, over a timespan of about 20 minutes, went offline. As a result international IP addresses were unavailable from Egypt.


Image taken from renesys.com / The following plot shows the number of available networks for each of the significant providers, between 22:00 and 23:00 UTC last night (midnight to 1am Cairo time). Our new observation is that this was not an instantaneous event on the front end; each service provider approached the task of shutting down its part of the Egyptian Internet separately.
Telecom Egypt (AS8452), the national incumbent, starts the process at 22:12:43. Raya joins in a minute later, at 22:13:26. Link Egypt (AS24863) begins taking themselves down 4 minutes later, at 22:17:10.
Etisalat Misr (AS32992) goes two minutes later, at 22:19:02. Internet Egypt (AS5536) goes six minutes later, at 22:25:10.

The New York Times called it "Egypt, to an unprecedented extent, pulled itself off the grid." and Jim Cowie, chief technology officer of Renesys said “In a fundamental sense, it’s as if you rewrote the map and they are no longer a country.”

The controle of internet content as well as accessibility is not new. Countries around the globe have developed different methods to do this. The most prominent examples are China or Iran, where twitter in 2009 played an important role in organising the political protests as well as distributing information after a disputed election. Earlier single-blogs coverage on mashups HERE.

As part of the New City Landscape (NCL) project we are collecting location based tweets in urban areas. For the last week we also recorded twitter activity in Cairo. And surprisingly twitter activity does not reflect the sudden drop off of international internet connection from Egypt. There is no dramatic reduction of tweets, however there is a continuous reduction of tweets reflected in the data. Over the past five days the location based twitter activity in Cairo has gone from about 250 to 300 messages per hour on Tuesday 27th and Friday 28th down to spikes of 50 on Monday the first of February.


Graph by single-blogs / Tweets collected using the TOM tool written by Steven Gray. The tool collects geolocated tweets originating within a 30km radius around the centre of Cairo. The graph shows number of tweets sent per hour.

This is not exactly as expected. There are different possible explanations for this. One of them could be that the internet is a difficult beast to tame and a few routers down don't mean the end of this versatile construct. Via very slow channels it must in this case still be possible to send mainly mobile tweets, even though mobile networks were also reported partially down.

Then on the first of February new information circulated the news channels. Google has put live a new service to allow people in Egypt to tweets via a phone call. After calling a speciall number, +16504194196 , +390662207294, +97316199855, a message can be left that will be posted as a tweet including the hashtag #egypt. The tweet will contain a link to the recorded message. Messages are pushed through this speakToTweet account. Somehow a very political move "We hope that this will go some way to helping people in Egypt stay connected at this very difficult time. Our thoughts are with everyone there."

Regarding out NCL collection this would not change anything since we are only looking at actual geolocated tweets send with Lat/Lon information included.

According to Renesys, Egypt has just this morning around 09h32 UTS returned to the internet after an absence of almost a week. How this will affect the tweeting activity we will see by tomorrow. It will be interesting to see weather this brings back up the numbers to a level of around 100 tweets per hour, we will see. New data and NCL maps are under way.


Image taken from renesys.com / All major Egyptian ISPs appear to have readvertised routes to their domestic customer networks in the global routing table, with the exception of Noor Group (AS20928). Recall that Noor was the exception (until Monday) to the Internet blackout, so they are as much an anomaly in restoration as they were in outage. (Update: Noor group back online with a full complement of prefixes as of 12:52pm Cairo time. Better late than never.)

Twitter Art Network - the Big Players

Twitter as an information service has developed rapidly since 2009. Most institutions have by now adopted a twitter account to distribute news and stay in touch with an audience.
Especially in the art world museums and galleries started using the social networking platform, creating important nodes in the twitter univers.

Some art institutions managed to attract a large fellowship with the @Tate for example having about 216,308 followers or the @MoMa with 388,670 followers.


Graph by single-blogs / Major art museums have adopted twitter as a networking and news channel tool. This art institutions twitter social network is constructed from @ tweets and RT tweets as a directed network graph.
Data collected using 140kit and visualised using gephi.

Of course now of interest is how these nodes link in to the wider twitter network and also how they link to each other. There are of course a number of different interests colliding and this reflects the stiff competition to some extend.

From the most recent 2000 twitter messages by each institution a social network graph was generated to visualise how some of the top museums are connected through activity in tweet terms. The graph represents how the institutions interact with other users and how this connects them into an entangled social network.


Graph by single-blogs / Zoom in on details around the New Yorker museums MoMa, New Museum, Guggenheim and the SFMoMa,

The nodes represent twitter users and the edges, connection lines, are established through @ tweets, a public direct message at some other user(s). The second indicator for established connection are the RT, the retweeting of messages by others.

Interesting to see is how the institutions have rather few direct links, but share quite a bit of intermediate twitter users. Especially between the american institutions there are quite some established connections, but also links across the atlantic are establish. Explore the graph in details below using the Google Maps style navigation.

Art Institutions Social Network

Graph by single-blogs using the GMap Image Cutter / Art Institutions Social Network - Use the Google Maps style zoom function in the top left corner to zoom into the map and explore it in detail. Click HERE for a full screen view.

You can check out the institutions involved on twitter for detailed info on the tweets.
@ZKM, @newmuseum, @tate, @MoMa, @sfmoma, @MOCAlosangeles, @vanabbemuseum, @ModernaMuseet, @mori_art_museum, @centrepompidou, @metmuseum, @guggenheim, @maspmuseu, @V_and_A, @NationalGallery, @npglondon, @_TheWhitechapel

NCL Social Networks

The New City Landscape maps NCL based on twitter messages sent in urban areas represent only one aspect of the data that was collected. For the maps we were focusing on the location at the moment of sending the message.

Now we are looking into the social network of the same data set and visualise how users communicate and how they are interconnected. Using the @'s and RT's in te messages a network was constructed establishing links between users that send directed tweets or retweet someone else's message.

Very quickly these social networks become extremely complicated and computational intensive. The old MacBook here is struggling with the larger networks of London and New York, were there are 20000 or 40000 nodes respectively to be calculated.

However the smaller networks of Paris and Munich draw very nicely in Gephi, the open source graph visualisation software used to render the following images.

The data we are using here was collected over the period of one week and the selection criteria is the geo location. It is a 30km radius around an urban area. This forms the starting point of the network with all the users within this set as seed nodes. Who ever they were in touch with is then added as a secondary node drawing the edges between these nodes.

Munich NCL social network with one very big player standing out, ProSieben. This is one of the big German TV channels.


Image by single-blogs / Social network of Munich twitter users corresponding to the Munich New City Landscape map.
The network is derived from @ and RT twitter messages.
This draws to 772 nodes and 1193 edges.

See the corresponding NCL map HERE.

Paris NCL social network

Image by single-blogs / Social network of Paris twitter users corresponding to the Paris New City Landscape map.
The network is derived from @ and RT twitter messages.
This draws to 4959 nodes and 7390 edges.

And a zoom into the Paris twitterNetwork map (bottom right), showing how the main nodes are linking down to smaller one of nodes.


Image by single-blogs / Zoom of social network of Paris twitter users corresponding to the Paris New City Landscape map.
The network is derived from @ and RT twitter messages.
This draws to 4959 nodes and 7390 edges.

See the corresponding NCL map HERE.

The NCL maps cover a lot more cities, see the world map HERE. As these are processed we'll be showing them here on the bog so stay tuned, some exciting network graphs will come up.

Worldwide Twitter Traffic

Twitter communications span the globe and the pinpointing of end locations of conversations in this animation shows how the network spans around the planet. It jumps between the hot spots of cities and even continents.
In the description of the project the authors discuss the rather interesting point of the meaning of 'Location in the case of twitter. In fact this not only applies to twitter but many location based services, the here is not always here. "'Location' has 2 meanings in the world of Twitter. It can mean (1) where someone was when they tweeted provided they are using a GPS-enabled smartphone, or (2) where someone lives (users can specify their home location)." (Geography 970)



In a second version the locations were mapped on a rotating globe which give a good impressionof how we communicate around an axis. For details please see Geography 970.

New City Landscape - the World View

The collection of NCL maps of Urban Areas is growing fast and it is getting difficult to keep track of all the cities we have covered so far. The NCL maps show a virtual landscape generated from geo located tweets sent from within a 30 km radius of the urban centre. In fact, so far we have in order of appearance:

New York, London, Munich, Paris, Moscow, Sydney, San Francisco, Barcelona, Denver, Hong Kong, Beijing and Chongqing. Further more the urban areas that need processing are: Shanghai
New Delhi, Chicago, Vancouver, Rio de Janeiro, Tehran, Tokyo, Jakarta, Sao Paulo, Toronto, Oslo, Basel, Rome, Guongzhou, Mumbai, Bangalore.

To provide a better overview here is a NCL world map with links to the individual locations. A link is provided to click through to the interactive and zoomable version of the individual urban area map. This will allow to explore the city of interest in more detail.


For a large scale map click HERE.

The data collected from the different cities varies quite a lot and especially the number of geo located tweets is a sort of tricky parameter. It does not correlate with the number of messages sent. The dependencies are more complicated and link probably more to the living standards and income. For example urban areas such as Jakarta and Sao Paolo have high numbers of twitter messages sent, but very few lat/lng referenced messages. This is more to be related to the coverage of smart phones and data charges, where people tend to use the twitter service over a broadband internet connection for free.

However, it is interesting to note that the number of geo located messages sent per unique user tend to be around 10 over the period of one week. Some areas go up to 15 or down to 8, but it is fairly constant across the board.


Image by single-blogs for NCL / The graph is showing the urban areas covered so far in the New City Landscape project, were we generate an activity landscape of an urban area using twitter data. The comparison shows vertical: percentage of geo referenced tweets, horizontal: average geo tweet sent per user, size: number of unique user, lable: urban area code.

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.