Masters of Networks 3 (more info) kicks off in a month. We at Wikitalia are hard at work to prepare the data; what can we learn by looking at online communities as networks of interactions? Is there a “signature of collaboration”, some characteristic that you can measure, like you would take a person’s temperature to figure out if she is well? The question is very exciting; and we do not believe it can be addressed by a small cadre of specialist. Instead, we have designed MoN3 as a natively interdisciplinary event, where online community managers, networks scientists and collective intelligence researchers work together to generate and formalize intuitions. The first batch of people who answered the call is super interesting: they come from all over the world, and represent an incredible talent pool.
- Jean-Michel Cornu (Imagination4People – Canada)
- Lee-Sean Huang (Purpose – USA)
- Noemi Salantiu (Edgeryders – UK)
- Jasminko Novak (EIPCM – Germany)
- Rosa Strube (CCSCP – Germany)
- Guy Melançon (University of Bordeaux- France)
- Benjamin Renoust (NII – Japan)
- Raffaele Miniaci (University of Brescia – Italy)
- Matteo Fortini (University of Bologna – Italy)
- Giovanni Ponti (University of Alicante – Spain)
- Alberto Cottica (Edgeryders – UK)
Collective Intelligence researchers:
- Mark Klein (MIT – USA and University of Zurich – Switzerland)
- Benoit Gregoire (Imagination4People – Canada)
- Marc-Antoine Parent (Imagination4People – Canada)
- Luca Mearelli (Wikitalia – Italy)
- Marta Arniani (Sigma Orionis – France)
- Fabrizio Gasparetto (Oxway – Italy)
- Mathias Becker (EIPCM – Germany)
MoN3 takes place in Rome, on March 10-11 2015. We will work out of the stunning location of Hotel Capo D’Africa, a stone’s throw from the Colosseum. The working language is English. Participation is free (and we throw in the lunch and as much coffee as you can drink), but we have to cap it at 20 attendees or so: this means we still have a few places. First come, first served: registration can be done here. If you think you absolutely need to attend, but cannot afford it, let us know and we will see if we can help.
During the summer, the Wikitalia group worked hard to improve Edgesense, the tool for real-time network analysis we are building as a part of the CATALYST project. As we worked on out “official” test bed community, that of Matera 2019, I happened to tell about it to Salvatore Marras. He proposed to deploy Edgesense on Innovatori PA. Edgesense is a very raw alpha, but the curiosity of trying it on a much larger community han the one in Matera (over ten thousand registered users) made us try anyway.
Surprise:despite using the same software as Matera 2019 (Drupal 7), Innovatori PA is not just bigger: it is really different. Even greater surprise: Edgesense allows you to literally see the difference with the naked eye (click here for a larger image with an English caption).
Metrics confirm what the eye sees. Innovatori PA, with over 700 active nodes (active means they wrote at least one post or one comment), gives rise to a rather sparse network with only 1127 relationships. Average distance is quite high, 3.76 degrees of separation (Facebook, with a billion-plus users has only 4.74 – source); modularity, the simplicity with which the networks partitions into subcommunities, is very high.
Conversely, the Matera 2019 community gives rise to a quite dense network: 872 relationships, so 80% of those in Innovatori PA, but with fewer than a third of its active users. Degrees of separation are 2.50, and modularity much lower.
If you want to play with Edgesense – among other things it helps to see the growth of the network over time – go here for Matera2019. No need to install anything, you access it with your browser. I recommend the tutorial we prepared to teach basic network analysis for online communities (click on the “tutorial” link top right in the page. The Innovatori PA installation is still being tweaked; I will update this post as it becomes available.
For over a year now I have been working on setting up a project to build a system for the improvement of online community management. I am convinced that this is critical to improve governance, because online communities are the easiest and cheapest way found yet to mobilize collective intelligence –and , especially in times of crisis, collective intelligence itself is the best card government institution can play to improve their abilities to manage large quantities of information and make good decisions. The project is provisionally called Dragon Trainer (I know, it’s nerdy, we will change it): it comes from the fact that getting an online community to perform a specific task (like exploring possible scenarios underpinning a public decision) is a bit like taming a large animal like a dragon: he is just too strong to boss around, so you need to design for the desired behavior to emerge. The main idea is to put at the disposal of public sector online community managers network analysis systems which are sophisticated yet simple to interpret, and that read directly the communities’ databases. This far, only large corporate platform like Facebook have these systems at their disposal: but that information is not shared with users, and then I don’t think these platforms are accountable enough to host public sector projects.
This endeavor was embedded into a broader research project, that I help crafting out under the aegis of a Spanish tech company, 24amp. Fortunately this project was selected for funding by the European Commission; unfortunately, 24amp had to withdraw from the consortium for administrative problems – despite the winning proposal mentions me by name as work package leader.
We are going to fix this. The board of Wikitalia (an Italian nonprofit for open government, inspired by Code for America) has decided to build Dragon Trainer as a new component of its smart governance suite. The project’s goals are fully consistent with those of Wikitalia: increasing the smarts, the openness and the collaborative nature of governance, especially local governance. I joined Wikitalia’s board to help just with that, so I will be following this project myself on behalf of the organization.
In the weeks to come I will explore possible paths for making this happen. My first goal is to build a (small) international partnership and raise the funding to develop both the code and the science underpinning it. What I would like is just a little money – the normal cut of European funded research, in the millions of euros, is way too large for this – but as free as possible from red tape and administrative duties: you give us money, we build the app. If you want to know more or get involved, you can watch the presentation video, join the Dragon Trainer Google Group or just write to me directly: alberto [at] cottica [dot] net.