Stefanie Posavec information designer - video interview

https://vimeo.com/30844155

When envisaging a typical data visualiser at work, you’d probably conjure up images of a person slaving over rows of numbers and wrangling spreadsheets. But Denver-born and London-based data designer Stefanie Posavec is of a different breed. Rather than simply turning a set of numbers into an information graphic, she finds data in things we wouldn’t normally associate with this type of information.

Read the whole Profile here - prote.in/profiles/stefanie-posavec

Sentence Drawing: Function vs. Art

http://trinkerrstuff.wordpress.com/2013/12/08/sentence-drawing-function-vs-art/

I recently was reading the book “Functional Art” and came across the work of Stefanie Posavec. Her Sentence Drawings (click here to see and click here to learn) caught my attention. Here is a ggplot2 rendition:

From what I understand about this visualization technique it’s meant to show the aesthetic and organic beauty of language (click here for interview with artist). I was captivated and thus I began the journey of using ggplot2 to recreate a Sentence Drawing...

Narrative Charts Tell the Tale…

http://blog.ouseful.info/2014/04/07/narrative-charts-tell-the-tale/

A couple of days ago, I got a message from @fantasticlfe asking if I’d done any tinkerings around what turned out to be “narrative charts”. I kept misapprehending what he was after (something to do with continuity?!;-), so here’s a summary of various graphical devices for looking at narrative texts that we passed back and forth, along with some we didn’t..

A Sankey diagram typically uses variable thickness lines to show flow between different elements in a system. (For this reason it’s often used to show energy flows throuygh a system, though it can also be used to good effect to show money flows.) The chart Michael linked to comes from xkcd:

netvizz v1.0 - facebook's

https://apps.facebook.com/netvizz/

Netvizz is a tool that extracts data from different sections of the Facebook platform (personal profile, groups, pages) for research purposes. File outputs can be easily analyzed in standard software.

For questions, please consult the FAQ and privacy sections. Non-commercial use only.

Big networks may take some time to process. Be patient and try not to reload!

Developing and hosting netvizz costs time and money. If the tool is useful for you, please consider to  

The following modules are currently available:

personal network - extracts your friends and the friendship connections between them

personal like network - creates a network that combines your friends and the objects they liked in a bipartite graph

group data - creates networks and tabular files for both friendships and interactions in groups

page like network - creates a network of pages connected through the likes between them

page data - creates networks and tabular files for user activity around posts on pages

netvizz – facebook to gephi

http://thepoliticsofsystems.net/2010/03/netvizz-facebook-to-gephi/

Since I have started to play around with the latest (and really great, easy to use) version of the gephi graph visualization and analysis platform, I have developed an obsession to build .gdf output (.gdf is a graph description format that you can open with gephi) into everything I come across. The latest addition is a Facebook application called netvizz that creates a .gdf file describing either your personal network or the groups you are a member of.

There are of course many applications that let you visualize your network directly in Facebook but by being able to download a file, you can choose your own visualization tool, play around with it, select and parameter layout algorithms, change colors and sizes, rearrange by hand, and so forth. Toolkits like gephi are just so much more powerful than Flash toys…

http://thepoliticsofsystems.net/wp-content/uploads/2010/03/facebook_rieder2_small3.png

What’s rather striking about these Facebook networks is how much the shape is connected to physical and social mobility. If you look at my network, you can easily see the Klagenfurt (my hometown) cluster to the very right, my studies in Vienna in the middle, and my French universe on the left. The small grape on the top left documents two semesters of teaching at the American University of Paris…

Update: v0.2 of netvizz is out, allowing you to add some data for each profile. Next up is GraphML and Mondrian file support, more data for profiles, etc…

Update 2: netvizz currently only works with http and not https. I will try to move the app to a different server ASAP.

Getting Started With The Gephi Network Visualisation App – My Facebook Network, Part I

http://blog.ouseful.info/?s=gephi+facebook&order=ASC

Gephi social network visualisation

Hello! I just did my first social network visualisation. Using Gephi, on recommendation from my colleague Ollie Glass. It was super easy! Gephi is free and is a piece of software like Photoshop which runs on PC or Mac. It also has a really nice tutorial, which I ran through straight away with no problems using their demo network/graph file.

But I wanted to do something with my own data. Firstly, to do the obvious. It’s been done many times but I wanted to make my own, editable network graph, of my Facebook network.

I managed to download my Facebook network graph file using the  netvizz facebook app as suggested by this blog post, which also looks useful but I haven’t read it all yet.

Simply opened that in Gephi and did the same method as in the tutorial, to see the groups of my friends and how they relate. I filtered it so smaller groups are not shown, and individuals with no mutual friends were not shown.

Although saving to SVG should have been able to be edited in Illustrator, that failed and Illustrator only opened a blank page. So, I saved as PDF and opened that PDF in Illustrator, to add my own labels to the groups.

Here’s the result! I’ve included the big file so you can zoom in to see the detail if you click it.

My Facebook network. Click to see a big version.

Big blobs are those with more ‘connectedness’. This doesn’t necessarily mean more mutual friends, it’s to do with shortest distance between different nodes.

Update: I did a better version, this time where blob size does reflect number of mutual friends. I also increased gravity and played with the repel and attract numbers.