Our Pythagorean World

Crystals like the flourite, calcite, or garnet here show properties, that can easily be expressed in mathematical terms. Social behavior seams to be random, however, data science can help us detect laws and patterns, that can be expressed in mathematical functions like the shape of the crystals.
Crystals like the flourite, calcite, or garnet here show properties, that can easily be expressed in mathematical terms. This inspired the legendary Pythagoras an his students to postulate the whole world to be genuinly mathematical. Social behavior seams to be random, however data science can help us detect laws and patterns, that can be expressed in mathematical functions like the shape of the crystals.
Our senses are adapted to detect of our environment, what is necessary for our survival. In that way, evolution turns St. Augustin’s postulate of our world as being naturally conceivable to our minds from its head onto the feet. What we define as laws of nature are just the mostly linear correlations and the most regular patterns we could observe in our world.

When I had my first computer with graphical capabilities (an Atari Mega ST) in 1986, I, like everybody else, started hacking fractals. Rather simple functions produced remarkably complex and unpredictable visualizations. It was clear, that there might be many more patterns and laws to be discovered in nature, as soon as we could enhance our minds and senses with the computer – structures and patterns way to subtle to be recognised with our unarmed eye. In that way, the computer became, what the microscope or the telescope hat been to the researchers at the dawn of modernity: an enhancement of our mind and senses.

“Number is an extension and separation of our most intimate and interrelating activity, our sense of touch” (McLuhan)

The origin of the word digital stems from digitus, Latin for the finger. Counting is to separate, to cluster and summarize – as Beda the Venerable did with his fingers when he coined the term digit. With the Net, human behavior became trackable in unprecedented totality. Our lives are becoming digitized, everything we do becomes quantified that is, put in quants.

With the first graphically capable computers, we could suddenly experience the irritating complexity of the fractals. Now we can put almost anything into our calculations – and we find patterns and laws everywhere.

What is quantified, can be fed into algorithms. Algorithms extend our mind into the realm of data. We are already used to algorithms recommending us merchandise, handling many services at home or in business, like supporting our driving a car by navigating us around traffic jams. With data based design and innovation processes, algorithms take part in shaping our things. Algorithms also start making ethical judgments – drones that decide autonomously on the taking or sparing the life of people, or – less dramatic but very effectiv though – financial services granting us a better or worse credit score. We have already mentioned “Posthuman Advertising” earlier.

The world is not only recognisable, the world in every detail is quantifiable. Our datarized word is the final victory of the Pythagoreans – all and everything to be expressed in mathematics. Data science in this way leads us to a similar revolution of mind, than that of the time of Copernicus, Galileo and Kepler.

Social Network Analysis of the Twitter conversations at the WEF in Davos

The minute, the World Economic Forum at Davos said farewell to about 2,500 participants from almost 100 countries, our network analytical machines switched into production mode. Here’s the first result: a network map of the Twitter conversations related to the hashtags “#WEF” and “#Davos”. While there are only 2,500 participants, there are almost 36,000 unique Twitter accounts in this global conversation about the World Economic Forum. Its digital footprint is larger than the actual event (click on map to enlarge).

There are three different elements to note in this visualization: the dots are Twitter accounts. As soon as somebody used one of the two Davosian hashtags, he became part of our data set. The size of the notes relates to its influence within the network – the betweenness centrality. The better nodes are connecting other nodes, the more influential they are and the larger they are drawn. The lines are mentions or retweets between two or more Twitter accounts. And finally, the color refers to the subnetworks or clusters generated by replying or retweeting some users more often than others. In this infographic, I have labelled the clusters with the name of the node that is in the center of this cluster.

Networking at Davos – 1st day

Now, that the World Economic Forum at Davos has started, also the conversational buzz on Twitter is increasing. While yesterday news agencies and journalists dominated the buzz, this morning (data ranging from 10:15 to 11:40) clearly has been a Paulo Coelho moment. The following tweet has been the most frequently retweeted #WEF tweet:

The most mentioned accounts in this time frame have been the following: @paulocoelho (265 mentions and retweets), @jeffjarvis (81), @bill_gross (74), @davos (63) and @loic (39). Interestingly, these five most frequently mentioned accounts did not contribute much to the Davos related Twitter conversations: Paulo Coelho mentioned #WEF in a tweet that has been resounding in the analyzed time frame and Jeff Jarvis did post three tweets. Here’s a visualization of the Twitter users mentioning each other. The larger a node, the more often it has been mentioned by other users.

If we take a look at the content, the most frequently mentioned words have been: wef (1001 times), davos (886), rt (= retweet, 827), need (301 times) and going (281 times). The last two words are clearly related to Paulo Coelhos tweet mentioned above. Other interesting words that have been connected to WEF and Davos are: crisis (89 times), world (88), bankers (61), responsibility (57), people (55), refuse (55), CEO (51) and fear (49):

Networking at the DLD conference (Part II)

As promised, here’s the second part of the DLD conference network analysis. We left the conference Monday afternoon. The remaining day looked like this:

The conference account @DLDConference and Idealab founder @Bill_Gross still are the most important Twitter discussions nodes in terms of PageRank. But there are also some new names and clusters in this map, for example enterpreneur Martin Varsawsky (@martinvars), the NGO @ashoka and BestBuy CTO @rstephens. On Tuesday, it looks quite different. This clearly has been Jeff Jarvis’ day. Not only did he take Bill Gross’ place but also overtook the official DLD conference account. But he hasn’t been the only new influencer today: Wikipedia’s Jimmy Wales, Huffington Post’s Arianna Huffington and Facebook’s COO Sheryl Sandberg also were important nodes in the DLD Twitter conversational network.

Here’s the map for the final DLD day:

Visually spoken: The conference is starting to dissolve. And people are moving on to Davos and getting ready for the World Economic Forum there.

Networking at Davos – getting ready for the WEF [updated]

The same thing that can be done for the DLD conference in Munich can of course be done for the WEF in Davos. This gives us a good opportunity to compare pre-conference and conference buzz of the two gatherings and compare actors, topics and network structures. Here’s a first glance at the Twitter conversation network for the hashtags #WEF and #Davos (recorded from Mon 7:15 pm to Tue 11:30 am):

One thing is very obvious from this structure: The WEF is much more of a news media event than the DLD (see the visualization of the DLD network from the day before the event). There are two very densely populated clusters of journalists from Reuters (red in the top right of the map) dominated by @rtrs_biztravel, @reuters_davos and journalist @reuters_davos and another BBC cluster (light brown on the right) dominated by @bbcworld. And there is also the guardian (deep blue on the bottom left) Other actors that have influential network positions are @worldbank and (this could become interesting) @occupy_wef. All in all the buzz generated by #WEF and #Davos appears to be significantly larger than the DLD related buzz.

Most frequently mentioned are: @davos (222 mentions), @bbcworld (94), @worldbank (58), @reuters_davos (49) and @wef (44). Most active users are Bloomberg’s @tomkeene (16 Davos tweets), @loupo85 (10), journalist Ken Graggs @betweenmyths (8), Reuters Social Media editor @antderosa (7) and Schwab Foundation @schwabfound (7).

UPDATE: And here is the first update to the network graphic. The data is now covering Tue 11:30 am to Tue 6:15 pm. That’s 1,600 tweets within 6.75 hours. So, the pace is clearly accelerating. For the first WEF analysis, we analysed 1,600 tweets within 16.25 hours. Now let’s take a look at the resulting network diagram:

Now, the Reuters and BBC clusters that dominated the Twitter discussions in the morning, have somewhat dissolved. Instead, there are new clusters centering on Bloomberg (light green and pink on the right), Angela D. Merkel (violet bottom right) – which by the way is not the official account of the German chancellor -, Yunus centre (violet at the top), Scott Gilmore (green at the top) and a very dense minicluster of Turkish EU affairs minister Egemen Bagis and Ozlem Denizmen (green at the top left). So it’s definitely starting to get more political 😉 The Occupy WEF cluster has been joined (structurally) by Amnesty WEF and has been connected (or interwoven) to the former Reuters cluster.

Here’s a list of the most frequently mentioned Twitter accounts in conversations with the hashtags “#WEF’ or ‘#Davos’: @davos (109 mentions), @ozlem_denizmen (45), @bloombergnews (43), @egemen_bagis (39) and @wef (36). The most active conversationalists are: @competia (12 posts), @antderosa (11), @mccarthyryanj (9), @wfp_business (9) and @sachailichopra (9).

Networking at the DLD conference

A rather traditional application of network analysis is taking a look at conference talk on social networks such as Twitter. Right now, Burda’s DLD conference in Munich is the best research object for this purpose – especially because Twitter’s CEO Jack Dorsey is one of the speakers. I began my tracking of conference on the day before. I thought it would be rather interesting to compare pre-conference and conference chatter in terms of the volume of buzz and the most influential people or accounts. So, here’s a look at the buzz up to Saturday, the night before the official conference launch:

Obviously, the activity is quite limited and the official account of the conference, @DLDConference, is the most frequently mentioned Twitter account (129 times) followed by @marcelreichart (24 times) who is one of the hosts. Other people who have been mentioned more than once are @sinaafra (12), @bill_gross (7) and @yokoono (7):

If we switch the perspective from the people most frequently mentioned to the most active people, suddenly there is a quite different set of Twitter users with aninanet (60 tweets), livestream (11) and idit (10) most frequently tweeting about “#DLD12”. Here’s the information in a bit more structured format:

Now take a look at the next visualization that captures the Twitter activity from afternoon to midnight on the first DLD day: The difference to the first network is striking. Now, @DLDConference has lost some influence – which is good because it’s not a good sign if the official conference account is the only one posting Tweets about a conference. And there are new people who are mentioned very frequently: @DLDConference (106 mentions), @bill_gross (84), @jack (70), @martinvars (31) and @jeffjarvis (31). The most active users were @jessicascorpio (15 tweets), @powercoach (14) and @DLDconference (12).

The size of the nodes in this visualization is the account’s page rank. The higher the page rank the higher the probability of reaching this node by chance while traveling through the network. Nodes with a high page rank have a high influence in the network. Nodes with a very high page rank were: @DLDconference, @lindastone, @hlmorgan and @bill_gross. The width of the arrows reflects the number of times one Twitter account has mentioned or retweeted another account. The strongest links were: @powercoach mentioning @jack, @burda_news mentioning @DLDConference and @mammonaetheevil mentioning @alecjross.

Finally, here’s a quick glance at the network for Monday. All DLD-related tweets from 0:00 until 16:00 have been counted and analyzed. The network is getting more and more dense.

Tomorrow I’m posting another update with the remaining Monday and Tuesday tweets and I’ll take a look at the content posted by the users. Read the update in part 2 of the article.