Paolo blog: Ramblings on Web2.0, Trust, Reputation, Recommender Systems, Social Software, Free Software, ICT4D and much more

According to stats published by Facebook, Facebook has currently 400,000,000 active users. This would make it the third most populous country in the world, after China and India.
Do you bet it will overtake India’s population (1,166,900,000)? In how many months?
(picture adapted from this image)

Attending the great conference Le reti socievoli (sociable nets) at Larica group of Univ Urbino.
Behind the speakers, the beamer shows live tag clouds of twitter posts (hashtag: #retisocievoli) by visibletweets (embedded below). Good example of audience live-participating to a conference!
I’ll make my first try to livetwitter a conf. Follow me at http://twitter.com/phauly.

By Debra Lauterbach; Hung Truong; Tanuj Shah; Lada A. Adamic
Download as PDF

Abstract: Reputation mechanisms are essential for online transactions, where the parties have little prior experience with one another. This is especially true when transactions result in offline interactions. There are few situations requiring more trust than letting a stranger sleep in your home, or conversely, staying on someone else’s couch. Couchsurfing.com allows individuals to do just this. The global CouchSurfing network displays a high degree of reciprocal interaction and a large strongly connected component of individuals surfing the globe. This high degree of interaction and reciprocity among participants is enabled by a reputation system that allows individuals to vouch for one another. We find that the strength of a friendship tie is most predictive of whether an individual will vouch for another. However, vouches based on weak ties outnumber those between close friends. We discuss these and other factors that could inform a more robust reputation system.

Notes: Can an online social network build enough trust to allow strangers to sleep on each others’ couches?

From http://smallblue.research.ibm.com/projects/snvalue/

The goal of this project is to integrate financial capital, human capital and social network analysis to formally and quantitively define and model social capital. Our interest is to find out what are the real dollar value of social networks.

Nine hundred and forty-eight dollars.

That’s the annual dollar value of each person in your email address book at work, according to a novel IBM study published in the Winter Information Systems Conference in February 2009.

IBM researchers, together with researchers in MIT, were looking to scientifically determine how valuable electronic social networks are, such as those in a group that primarily communicates electronically. Using mathematical formulas, honed by observing the email traffic and financial success of 2,600 anonymized far flung IBM consultants collaborating on thousands of projects during one year, researchers found that not all email relationships were equal.

In fact, they found that people with strong email ties with a manager, or had a more diverse circle of correspondents, enjoyed greater financial success than those who were more aloof. Teams with an even mix of genders also performed well financially. Individuals have more diverse networks and thus have more people who are reachable within 2 social steps (i.e., your friends’ friends’ friends.) is valuable. Too intensive communications to the same people have negative impact, perhaps because of the repetitive redundant information exchange.

From the “social network” page on Wikipedia:

Some researchers have suggested that human social networks may have a genetic basis.[15] Using a sample of twins from the National Longitudinal Study of Adolescent Health, they found that in-degree (the number of times a person is named as a friend), transitivity (the probability that two friends are friends with one another), and betweenness centrality (the number of paths in the network that pass through a given person) are all significantly heritable. Existing models of network formation cannot account for this intrinsic node variation, so the researchers propose an alternative “Attract and Introduce” model that can explain heritability and many other features of human social networks.[16]

[15] # ^ “Genes and the Friends You Make”. Wall Street Journal. January 27, 2009. http://online.wsj.com/article/SB123302040874118079.html.
[16] # ^ Fowler, J. H. (10 February 2009). “Model of Genetic Variation in Human Social Networks” (PDF). Proceedings of the National Academy of Sciences 106 (6): 1720–1724. doi:10.1073/pnas.0806746106. http://jhfowler.ucsd.edu/genes_and_social_networks.pdf

The typical example of a socio-technical system heavily influenced by its user (prosumer!) is Flickr. Maybe not too many people know that in the beginning Flickr was a Web-based game, called Game Neverending (GNE). Best summary of early Flickr history I found is in this interview.

The original interface of GNE (see below) was heavily based on Instant Messagging. You could drag game objects into an IM conversation and it would send to all the other members of the chat an image of the object.
THAT was the key feature! The creators of GNE thought “what if instead of game objects, you could drag and drop other digital objects into these conversations, like Word documents, or PDFs? Or maybe photos?”
So the first version of Flickr was just a stripped-down Game Neverending interface, with photos instead of game objects.

I think this is the perfect example of user-driven design. “I created a web game site –> users use it for sharing objects –> then I create a site for sharing photos.”

A screenshot of Game Neverending (from GNE Museum)

And there was also a Social network explorer!

Interesting blog post by Cameron Marlow, research scientist at Facebook over at overstated.net: Maintained Relationships on Facebook.

They start from a simple question: is Facebook increasing the size of people’s personal networks?

They looked at the communications of a random sample of users over the course of 30 days and defined networks in 4 different ways:

• All Friends: the largest representation of a person’s network is the set of all people they have verified as friends. In research papers this number ranges between 300 and 3000. In facebook on average every users has 120 friends.
• Reciprocal Communication: as a measure of a sort of core network, we counted the number of people with whom a person had had reciprocal communications, or an active exchange of information between two parties. In research papers, this numbers ranges from 3 as individuals with whom I can discuss important matters (for Americans) to 10 or 20 as ongoing contacts at a university.
• One-way Communication: the total set of people with whom a person has communicated.
• Maintained Relationships: the set of people for whom a user had clicked on a News Feed story or visited their profile more than twice. This is a sort of over-the-shoulder relationship, I’m “following” (this is the relationship type) the target user without she necessarily knowing it. This is a new type of relationship (not really available says 50 years ago), similar to reading the flow of thoughts of someone via a blog or just looking at the pictures uploaded on Flickr.

An interesting observation: “as a function of the people a Facebook user actively communicate with, you are passively engaging with between 2 and 2.5 times more people in their network”.

And another one: The stark contrast between reciprocal and passive networks shows the effect of technologies such as News Feed. If these people were required to talk on the phone to each other, we might see something like the reciprocal network, where everyone is connected to a small number of individuals. Moving to an environment where everyone is passively engaged with each other, some event, such as a new baby or engagement can propagate very quickly through this highly connected network.