When I started developing SocNetV back in 2005 the term “social network” had a simple sociological meaning; any group of somehow “connected” actors, which might interest a sociologist to study and analyse in terms of their social properties and patterns (centralities, triads, etc). The actors can be of any type (humans, animals, organisations, companies etc) and so the cause of them being connected: working in the same place, belong to the same hive/group, mentioning each other, having commercial relations etc. Thus the main reason behind developing SocNetV was to create a simple “point and click” application that would enable the researcher to load his real-life gathered data and visualize/analyze the network properties. Or, in case the network was small enough, perhaps recreate it with some clicks on a canvas before analysing it. Back then it had never occurred to me that the same “social network” would be used now-days to describe online communities of million of users. As a matter of fact, I always thought that this strand of sociology is more meaningful in analysing relatively small groups rather than thousands of interconnected actors. Nevertheless, the term is used now this way too and this means that Social Network Analysis software such as SocNetV face a new problem: people not knowing anything about Social Network Analysis as a hybrid sociology-mathematics discipline think that all the software does is to “automatically” analyse any given online virtual community; who is connected to whom and how. Which is certainly not true.
That being said, the question is whether you can use SocNetV with a virtual “social network” at all. The answer: Yes you can. For instance, you could analyse social interactions (i.e. mentions) between “friends” in that virtual network. Apparently, SocNetV cannot grab their link/connections data on its own (forget the built-in web crawler; it cannot get and parse private data), but if you can extract the data for yourself and transform them into a proper GraphML format, then SocNetV will happily load and visualise the virtual social network so that you can analyze its properties. This seems to be the case with Dolphin social network software, an open source platform for social networks. The guys behind the project kindly informed me that they are about to use SocNetV as an “intelligence” source for Dolphin-site operators. Dolphin and its mobile-friendly sibling Trident support social connections, conversations, locations and other social-graphs related data types, which can be used by SocNetV depending on operator needs. For example, “if an air-line company launches a social network for clients, they could use SocNetV to analyze connections between friends within network, trends of their discussions and posts, and then use that to plan which routes would be in demand and when. Later they could create special offers to relevant segments of the network and advertise it within their site”. Seems an interesting use for SocNetV. Kudos to boonex guys!
Christopher Ecclestone
Dimitris,
Interesting project you have undertaken. I had a specific need and wondered whether you thought your software might address it.
I am trying to create a social network of ancient Greeks who lived in the city of Antioch in the 4th century. I have lots of names and their relationships (familial, friends, patron/client, governor/bureaucrat) with each other now I want to create a diagram to show how they were linked.
You think this is doable? Welcome your thoughts
Christopher
Dimitris Kalamaras
Yes, it is feasible indeed to create social network diagrams with the said relationships of ancient Greeks. What is more, if the actors (ancient greeks) are a fixed-size group, you can create multi-relational diagrams and inspect the differences between them just by clicking on the next/previous relationship button. See an example here:
and the next relation:
jihbed
I very happy announced my first conference socnetv https://2014.rmll.info/conference165, video : https://rmll.ubicast.tv/videos/socnetv-un-outil-pour-lenseignement-et-lapprentissage-de-lanalyse-des-reseaux-sociaux/