Category Archives: Network Notebook

Semi-structured notes on my Ph.D. thesis work on network science. For an intro, see http://youtu.be/KKrM2c-ww_k

Masters of Networks 3: designing the future of online debate

Back in the day, the emergence of the global Internet was saluted with joy and hope by lovers of democracy. Many activists saw an opportunity for an electronic agora, endowed with always-on operations mode and total recall, that would finally deliver an Athenian-style participatory democracy at the planetary scale, and win power to the collective intelligence of people. It turned out things were not so simple. Online communities have been around for at least 30 years: some of them led interesting, deep debates, and even built amazing things like Wikipedia or OpenStreetMap; others, not so much. A large-scale participatory democracy is very far from being realized.

Masters of Networks 3: communities is an event that tries to learn from the experience of 30 years of online debate. Why is debate fruitful and creative in some contexts, sterile and conflictual in others? Are there reliable tests for a debate’s good health? Can we predict how conversations will evolve? We will tackle these questions starting from a key idea: any conversation, both on- and offline, is a network of interactions across humans, i.e. a social network. In the course of the CATALYST project, Wikitalia and its partners have built Edgesense, a simple software for real-time, interactive network analysis of online communities (video demo – example).

Masters of Networks 3: communities is a two-day hackathon for network scientists, active members of online communities and people interested in participatory democracy to get together, discuss these themes and make sense of what we already know about them. We will visualize and analize the networks of several online communities, using the deep knowledge of its active members and moderators as our guiding star; our goal is figuring out what a “healthy” conversation network looks like, and if we can tell them apart from the networks of “sick” conversations (too conflictual, superficial, polarized etc.).

Masters of Networks 2: communities happens in Rome on 10-11 March 2015. Several scientists, developers and community managers from the CATALYST project will attend, but we have set aside about ten places to allow any interested person to participate. In particular, if you are running an online community and would like to visualize and analyze its interaction network, we can probably help – get in touch and we will see what we can do. Participation is free, but registration is necessary – go here to register. The working language will be English.

I will be there. I think this is a central issue; I tried to argue as much in the video below

Networks, swarms, policy: travels across the weird, dark landscape of 21st century policy making

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I used to be an economist. Then in the two-thousands, I started to read about complexity science. I chased an intuition telling me networks are important (it was 2009, I still remember the epiphany when I saw the network analysis of interactions in Kublai) and started to study them. I was – still am – looking for a sort of Holy Grail: design and build online communities that can deploy collective intelligence to attack problems too complex for individuals (even very smart ones) or small groups to crack. To burrow deeper into the issue I had to re-learn some linear algebra and probability theory; and that unlocked paths entirely new to me, dark passageways across computational biology and experimental psychology.

The landscape got really strange, a far cry from the orderly, well-lit architecture of standard economics. Quite dangerous too: it’s full of philosophical traps (if it is really collective intelligence, will we individuals be able to recognize it? Would that not be like a neuron trying to understand the brain?) and even moral dilemmas (it is possible that the well-being of a system implies sacrificing its components, just like a species evolves killing off its weakest members: what happens if the system is society and we are its components? Do we sacrifice the whole or the parts?).

But here’s the craziest thing: I am not the only one wandering in this place, wherever it is. In the world of public policies, where I have worked for years, with every passing month I recognise new fellow travellers. I find myself talking of esoteric stuff like evolving networks, smart swarms, online ethnographies, variability engines. I feel like a sixteenth-century alchemist: we do stuff, it seems to work, we am not quite sure why but it works too well to be just random luck. We feel on the verge of an important discovery, something like the seventeenth-century scientific revolution. This weird, dark world is behind my talk at Personal Democracy Forum, held a month ago in Rome. If you want a taste, the video is below, both in the English original (left audio channel) and in Italian translation (right).

(Dedicated to Giulio Quaggiotto)

Making Edgesense: two online communities at a glance

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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.