When followers are not enough

[italian version]
We have just gathered a brand new datased of FriendFeed data (you can download it in the Data section, it’s named 2010-a dataset ). Since it is considerably larger than our previous database we decided to test few more hypotesis on information propagation in SNSs. One of the key concepts speaking about the ability to spread online information is that being well connected is a key element in propagation strategies. This point can be roughly summarised as: the more followers you have the more you can inform. We’ve already challenged this assumption before and we wanted to test it deeper.
Therefore we analysed the relationship between the actual number of followers and the average audience of every users. We defined the average audience value as the average number of users been exposed to the messages sent by a specific user during our sample time. Due to the technical structure of Friendfeed users that were able to start the most engaging discussions have a larger opportunity of have an actual audience larger that the simple list of their followers.

Followers /Avg Users

As it is shown in the graph – that shows only the top 20 users according to their followers number – there could be a huge difference between the followers and the actual audience that users can engage. It is very interesting to point out how the users with a larger average audience is ranked only 18th according to the followers number.
As we said before, when we’re dealing with social phenomena and users engagement (as it happens in online propagations): followers are not enough.[English version]
Partendo dall’ultimo dataset che abbiamo acquisito con i dati di FriendFeed abbiamo iniziato a testare alcune ipotesi relative alla possibilità di definire la capacità comunicativa degli utenti all’interno di questo tipo di reti. Una delle assunzioni che si sono fatte più spesso (più in passato di quanto non avvenga ora) riguarda il nuero di followers. In pratica si considera spesso questo valore come un indicatore della capacità comunicativa di un utente. Brutalmente si pensa che se una persona è in contatto con molte altre persone questi abbia la capacità di raggiungere una massa importante di utenti.
Per verificare questo assunto abbiamo deciso di osservare la relazione tra il numero di follwers e la audience media degli utenti. Con audience media intendiamo il numero di utenti che sono stati esposti ai messaggi postati da uno specifico utente durante il nostro periodo campione (2 Mesi: Agosto- Settembre 2010).
Followers /Avg Users

Data la natura di FriendFeed l’audience tenderà a crescere verso valori più ampi rispetto ai follower diretti tanto più l’utente sarà in grado di far partire discussioni che riescono a propagarsi ed a coinvolgere gli amici degli amici e così via.
Come si può vedere dall’immagine [che mostra il rapporto tra followers e audience media per i 20 utenti con il maggior numero di followers all’interno della rete di FriendFeed italiana (solo account pubblici)] un elevato numero di followers non significa necesariamente un’elevata audience media, anzi l’utente che – in termini assoluti – raggiunge mediamente un’audience maggiore si colloca solo diciottesimo quando andiamo a contare i followers.
Insomma ancora una volta quando parliamo di reti sociali i numeri possono ingannare facilmente.

Mapping FriendFeed Network: switching the perspective

Recently we’ve posted a visualisation of the Italian Network of FriendFeed. Such a map was an interesting and general perspective showing how a complex network can be visualised. Obviously when we’re dealing with social networks or microblogging sites we’re dealing with a complex network emerging from many different egonetworks. How is the perspective over the same Network (Italian Friendfeed Users) if we observe  it from the inside?
Starting from the same dataset we’ve used for the previous visualisation we generated an Egonetwork using as central user one of the minor nodes of the global visualisation. We chose the user lucamondini who, at that time, had a rather small network: 150 following and 200 followers. The idea was to see how the network looked like when the observer was one of the peripheral nodes.

An explanation of nodes sizes and colours can be found here, what’s interesting is that switching the perspective to this user’s point of view the overall scenario change. Even if it is always possible to find major and minor nodes they don’t seem to be necessarily the same nodes of the global map. Of course users that are very popular within the whole network seem to be quite popular also within local egonetwork but their specific size is different. Moving our observation to nodes that are even more peripheral (we chose the user magicabula, 21 followers and 33 following) – since it has so few followers this user wasn’t included into the global visualisation – will show a small network of highly connected users where some of the users are heavily connected even in the global map and some have a large authority only within this local perspective.
When we’re dealing with social network and information propagation we must keep in mind that the scenario might be really different when it is observed from the far periphery of the network.