[Italiano]
A group of Students from the School of Information and the School of Public Health of the Univeristy of Michigan have done some very nice visualisation work using our latest dataset. We’ve been in touch with Guangming Lang for some time to explain them the data structure and few insights and then they did the whole job.
The visualisations focus on sic questions: Where do FriendFeed users come from? What are the sources for entries on FriendFeed? How engaged are FriendFeed users? How engaged are FriendFeed users as time passes? What is most talked about in FriendFeed? and How do the top 90 most followed users gain followers?
Well, enjoy this very nice work.[English]
Un gruppo di Studenti della School of Information e della School of Public Health dell’Università del Michigan hanno appena pubblicato alcune visualizzazioni basate sul nostro dataset di FriendFeed.. Il tutto è iniziato qualche tempo fa quando Guangming Lang ci ha contattato chiedendoci alcune informazioni sulla struttura dei nostri dati che aveva appena scaricato e, dopo qualche tempo, ecco il risultato del lavoro.
Le visualizzazioni rispondono ad alcune domande molto interessanti:
– Where do FriendFeed users come from?
– What are the sources for entries on FriendFeed?
– How engaged are FriendFeed users? How engaged are FriendFeed users as time passes?
– What is most talked about in FriendFeed?
– How do the top 90 most followed users gain followers?
Insomma, veramente un ottimo lavoro!