Making Edgesense: two online communities at a glance

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.

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2 thoughts on “Making Edgesense: two online communities at a glance

    1. Alberto Post author

      Jeff, that would be so very interesting! There are strong preliminary indications that these connections are highly significant. For example, in the network analysis of the LOTE3 Twitterstorm you can see very well the three communities: Matera in green, to the left; Edgeryders in red, to the center; and Ouishare to the right, in blue. People bridging across communities (highly betweenness-central) are exactly the people you might expect, that play important roles on both sides: Elf etc.

      Turning this anecdotal evidence into systematic analysis would require a way to know who is who (computer scientists speak of “unique identifiers”). You, for example, can be “Bezdomny” on Edgeryders, but “bzdomny” on Twitter, and maybe “Jeff” on Ouishare. Once this problem has been overcome (and there could be ways, for example based on e-mail addresses), another one needs to be solved: we have perfect insight into Edgeryders because (1) we have full access to the Edgeryders database (we are technically enabled to do analysis) and (2) all data on Edgeryders are released with an open license (we are legally enabled to do analysis). With the collaboration of other communities, such an analysis could be done… in principle. In the case of Ouishare, I am told they use Facebook groups: by doing so, they effectively give Facebook the exclusive right to do this kind of analysis. Technically, Facebook has no APIs; legally, the IPRs on your content uploaded onto Facebook belongs to Facebook.

      Maybe a possibility would be to manually code the Edgeryders database for people that belong to other communities, such as yourself, Dorotea, Elf etc. At that point, you would have a network analysis of Edgeryders enriched with the special role of some people as “gateways” to other communities.

      I am happy to discuss any idea leading to this with anyone at Ouishare, or any community really. Should we take this conversation onto Edgeryders-Ouishare?

      Reply

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